| Commit message (Collapse) | Author | Age |
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Currently there are large number of tensors managed
by non-visitable memory allocators in CPU-only PS.
GPU workers seem less prone to this problem.
Copying large sized tensor buffers may introduce
non-trivial overhead. Should probably fix this.
Signed-off-by: Bairen Yi <byi@connect.ust.hk>
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The visitor pattern is used to allow pre-registration of memory for
DMA access, e.g. for fast GPU/CPU i/o and for RDMA networking. The
VisitableAllocator interface was introduced to support this use some
time ago, prior to SubAllocators. Memory registration works best if
it's done infrequently, on large pieces of memory, rather than on
every piece that's dynamically allocated/freed. This usage pattern
fits the SubAllocator better than a general Allocator. This change
moves memory allocation visitor access to SubAllocator and eliminates
the VisitableAllocator subclass of Allocator.
This change also more rigorously enforces the requirement that all
Visitors be declared prior to memory allocation begining. This is
accomplished by requiring that Visitors be provided to the SubAllocator
constructor.
This refactoring will ease an upcoming CL introducing
NUMA specific CPU devices. It also should fix some performance
pitfalls (e.g. accidental use of PoolAllocator) introduced by an
earlier refactoring of ProcessState that was also in preparation for
NUMA. It restores the default use of the cpu_allocator() value (i.e.
no SubAllocator) by model executions that don't use allocation
visitors (since visitor registration must precede the first allocation,
hence can be detected at that time).
PiperOrigin-RevId: 213505655
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PiperOrigin-RevId: 213394522
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The visitor pattern is used to allow pre-registration of memory for
DMA access, e.g. for fast GPU/CPU i/o and for RDMA networking. The
VisitableAllocator interface was introduced to support this use some
time ago, prior to SubAllocators. Memory registration works best if
it's done infrequently, on large pieces of memory, rather than on
every piece that's dynamically allocated/freed. This usage pattern
fits the SubAllocator better than a general Allocator. This change
moves memory allocation visitor access to SubAllocator and eliminates
the VisitableAllocator subclass of Allocator.
This change also more rigorously enforces the requirement that all
Visitors be declared prior to memory allocation begining. This is
accomplished by requiring that Visitors be provided to the SubAllocator
constructor.
This refactoring will ease an upcoming CL introducing
NUMA specific CPU devices. It also should fix some performance
pitfalls (e.g. accidental use of PoolAllocator) introduced by an
earlier refactoring of ProcessState that was also in preparation for
NUMA. It restores the default use of the cpu_allocator() value (i.e.
no SubAllocator) by model executions that don't use allocation
visitors (since visitor registration must precede the first allocation,
hence can be detected at that time).
PiperOrigin-RevId: 213371553
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PiperOrigin-RevId: 210432093
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Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
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PiperOrigin-RevId: 209679086
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Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
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This fix tries to address the issue raised in 21696 where
tensorflow failed to compile when both RDMA and GDR are on.
The issue is that the memory allocator of GDR used the same
name as RDMA.
This fix fixes 21696.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
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in preparation for using NUMA node specific allocators.
Also, add stub NUMA functions on the platform interface to
platform/windows/port.cc.
PiperOrigin-RevId: 205413998
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ProcessState is a singleton that anchors per-process resources.
Up until now that meant only GPU-related memory allocators
since CPU allocation was usually done directly from Allocator::cpu_allocator.
Accordingly process_state.h was in common_runtime/gpu and ProcesState
was only used in GPU builds.
With the upcoming introduction of NUMA node specific CPU allocators
it will be important that most of the TF runtime switch to requesting the
proper NUMA-specific CPU allocator. These allocators will be owned by
and obtained from the ProcessState singleton which will exist in all
builds. The GPU-specific functions are moved to a new
GPUProcessState, also a singleton.
PoolAllocator is also migrated out of common_rumntime/gpu into common_runtime.
PiperOrigin-RevId: 203002666
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PiperOrigin-RevId: 202585094
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Without this change, a shared resource (e.g. an Iterator) could not be
created in one session `s1`, and used in a later session `s2` after
`s1` was closed, because the iterator might indirectly capture devices
from the previous session, and use them after they are freed when the
`WorkerSession` was deleted.
The current change only affects the singleton "legacy" WorkerSession,
which is never deleted, but this is necessary to switch all sessions
to use separate WorkerSession objects.
PiperOrigin-RevId: 193541426
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PiperOrigin-RevId: 190878279
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PiperOrigin-RevId: 186073337
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tensorflow/contrib/.../*.{hh,c}.
PiperOrigin-RevId: 183855242
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Retried RecvTensorRequests are problematic because a RecvTensor with no
corresponding sender will wait forever, and the tensor may have been delivered
to a previous retry.
This change adds a unique request_id to each RecvTensor request, and we check
these request_ids against a set of recent request_ids. If a request_id is in the
recent set, we reject the RecvTensor request.
PiperOrigin-RevId: 182863245
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PiperOrigin-RevId: 174243882
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PiperOrigin-RevId: 173889798
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PiperOrigin-RevId: 173613863
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END_PUBLIC
---
Commit 1e1b3d902 authored by Pete Warden<pete@petewarden.com>
Committed by gunan<gunan@google.com>:
Changed output directory for Pi CI build to fix permissions problem with nightlies (#13257)
* Fix for RTLD_GLOBAL breakage of Pi builds, and removed Eigen version change for Pi that's no longer needed
* Fixed Pi Zero OpenBLAS build problems and tidied up directories used
* More robust checks in Pi build script
* Changed output directory for Pi CI build to fix permissions problem
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Commit fe3a2e65c authored by Yan Facai (???)<facai.yan@gmail.com>
Committed by drpngx<drpngx@users.noreply.github.com>:
check invalid string type for dest_nodes in extract_sub_graph (#13057)
* BUG: check str type
* TST: add unit test
* CLN: remove list check
* CLN: use warning
* CLN: 2 indent
* CLN: raise TypeError if not list
* CLN: check string only
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Commit 225ab7629 authored by Jean Wanka<jm.wanka@gmail.com>
Committed by Jean Wanka<jm.wanka@gmail.com>:
Fix polynomial decay with cycle for global step=0
For polynomial decay with cycle=True the learning rate at
step 0 becomes NaN, because in the process of calculating it we
devide by 0. This change should fix it, by setting the multiplier
for the decay steps to one for global_step=0.
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Commit 286f57061 authored by Bjarke Hammersholt Roune<broune@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Make Service::TransferToClient not attempt to manipulate the literal when the transfer failed, preventing a crash and allowing the caller to see the reason for the failed transfer.
PiperOrigin-RevId: 169770126
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Commit e0501bc4d authored by Yong Tang<yong.tang.github@outlook.com>
Committed by Shanqing Cai<cais@google.com>:
Fix GRUBlockCell parameter naming inconsistency (#13153)
* Fix GRUBlockCell parameter naming inconsistency
This fix tries to fix the issue in 13137 where
parameter `cell_size` is used instead of `num_units`.
This is inconsistent with other RNN cells.
This fix adds support of `num_units` while at the same
time maintains backward compatiblility for `cell_size`.
This fix fixes 13137.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
* Add `@deprecated_args` for 'cell_size' in `GRUBlockCell`
This commit adds `@deprecated_args` for 'cell_size' in `GRUBlockCell`
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
* Address review comment
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
---
Commit 02a2eba05 authored by Pete Warden<pete@petewarden.com>
Committed by gunan<gunan@google.com>:
Fix for RTLD_GLOBAL breakage of Pi builds, and removed Eigen version change that's no longer needed (#13251)
* Fix for RTLD_GLOBAL breakage of Pi builds, and removed Eigen version change for Pi that's no longer needed
* Fixed Pi Zero OpenBLAS build problems and tidied up directories used
* More robust checks in Pi build script
---
Commit 8ef722253 authored by Sanjoy Das<sanjoy@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Remove a redundant setName.
The EmitComputation should have emitted a function with the right name, so use a
CHECK instead.
PiperOrigin-RevId: 169764856
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Commit 1b94147dc authored by Neal Wu<wun@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fix broken GitHub links in tensorflow and tensorflow_models resulting from The Great Models Move (a.k.a. the research subfolder)
PiperOrigin-RevId: 169763373
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Commit b1ada5f0c authored by Justine Tunney<jart@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fix TensorBoard python -m invoke in docs
PiperOrigin-RevId: 169758752
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Commit 2957cd894 authored by Mustafa Ispir<ispir@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Local run option of estimator training.
PiperOrigin-RevId: 169756384
---
Commit 1dc2fe7ac authored by Gunhan Gulsoy<gunan@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
BEGIN_PUBLIC
Automated g4 rollback of changelist 166264198
PiperOrigin-RevId: 169998124
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PiperOrigin-RevId: 167401527
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END_PUBLIC
---
Commit 575bd01d4 authored by Vijay Vasudevan<vrv@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Remove /replica:0 declaration in device functions and allow them
to be freely bound based on cluster names present.
When more than one value matches, it will choose the first
lexicographically available device that matches the specification,
which in practice will do pretty much the same thing as hardcoding
/replica:0.
PiperOrigin-RevId: 165766815
---
Commit d685bbc54 authored by Alexandre Passos<apassos@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Benchmarks with backprop enabled (and removes overhead).
Before:
np.array([[3]]) took 1.50us (30000 iterations)
Tensor([[3]]) took 16.30us (30000 iterations)
MatMul [2, 2]: np.dot took 0.61us (30000 iterations)
MatMul [2, 2]: tf.matmul took 60.53us (30000 iterations)
MatMul [2, 2]: gen_math_ops.mat_mul took 25.72us (30000 iterations)
MatMul [2, 2]: TFE_Py_Execute took 2.82us (30000 iterations)
MatMul [2, 2]: defun(tf.matmul) took 45.70us (30000 iterations)
MatMul [100, 784]: np.dot took 383.32us (1000 iterations)
MatMul [100, 784]: tf.matmul took 350.35us (1000 iterations)
MatMul [100, 784]: gen_math_ops.mat_mul took 315.97us (1000 iterations)
MatMul [100, 784]: TFE_Py_Execute took 249.42us (1000 iterations)
MatMul [100, 784]: defun(tf.matmul) took 280.95us (1000 iterations)
If backprop is enabled:
np.array([[3]]) took 0.83us (30000 iterations)
Tensor([[3]]) took 15.21us (30000 iterations)
MatMul [2, 2]: np.dot took 0.63us (30000 iterations)
MatMul [2, 2]: tf.matmul took 76.31us (30000 iterations)
MatMul [2, 2]: gen_math_ops.mat_mul took 38.66us (30000 iterations)
MatMul [2, 2]: TFE_Py_Execute took 2.31us (30000 iterations)
MatMul [2, 2]: defun(tf.matmul) took 51.96us (30000 iterations)
MatMul [100, 784]: np.dot took 378.34us (1000 iterations)
MatMul [100, 784]: tf.matmul took 352.09us (1000 iterations)
MatMul [100, 784]: gen_math_ops.mat_mul took 364.28us (1000 iterations)
MatMul [100, 784]: TFE_Py_Execute took 350.68us (1000 iterations)
MatMul [100, 784]: defun(tf.matmul) took 377.19us (1000 iterations)
After:
np.array([[3]]) took 0.86us (30000 iterations)
Tensor([[3]]) took 15.19us (30000 iterations)
MatMul [2, 2]: np.dot took 0.60us (30000 iterations)
MatMul [2, 2]: tf.matmul took 64.51us (30000 iterations)
MatMul [2, 2]: gen_math_ops.mat_mul took 28.34us (30000 iterations)
MatMul [2, 2]: TFE_Py_Execute took 2.38us (30000 iterations)
MatMul [2, 2]: defun(tf.matmul) took 48.50us (30000 iterations)
MatMul [100, 784]: np.dot took 475.27us (1000 iterations)
MatMul [100, 784]: tf.matmul took 399.50us (1000 iterations)
MatMul [100, 784]: gen_math_ops.mat_mul took 307.80us (1000 iterations)
MatMul [100, 784]: TFE_Py_Execute took 272.83us (1000 iterations)
MatMul [100, 784]: defun(tf.matmul) took 350.06us (1000 iterations)
PiperOrigin-RevId: 165765641
---
Commit d902babbd authored by David Majnemer<majnemer@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[XLA] Algebraic simplifier incorrectly transformed convolutions into bitcasts
PiperOrigin-RevId: 165765575
---
Commit 8e78e10ef authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
disable test temporarily
PiperOrigin-RevId: 165763204
---
Commit a271c37db authored by Benoit Steiner<bsteiner@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Small improvements to the arithmetic optimizer
PiperOrigin-RevId: 165760972
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Commit b6409594d authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Convert some tests to cover both eager and graph.
PiperOrigin-RevId: 165760364
---
Commit 5ead76420 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Reduce XLA compile time by ~7% for a convolutional image model:
* Added CompactPointerSet<T>, which is optimized for set size <= 1.
* Changed expensive CHECKs to DCHECKS in buffer_assignment.cc
* Reserve space in DFS state array before starting DFS.
* Use unsigned arithmetic in DFS state maintenance.
* HloInstruction:
- Moved frequently used fields to start for better cache locality.
- Use InlinedVector instead of vector for operand array.
- Use InlinedVector instead of vector for DFS stack.
* Pre-compute "is array" and "is tuple" for LogicalBuffer.
* PointsToSet:
- Combine two ShapeTrees into one.
- Use CompactPointerSet instead of std::set to hold sources.
- Use CompactPointerSet instead of std::set to hold flattened buffers.
* ShapeTree: use unique_ptr instead of optional for shape storage
(reduces size and destruction overhead).
* Add proper const qualifiers to some FlatSet iterator methods.
Co-author=jeff
PiperOrigin-RevId: 165759117
---
Commit a0544b0b8 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Make TPU symbols more easily accessible from contrib.
PiperOrigin-RevId: 165753322
---
Commit cdc08afbb authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Slightly relax numeric tolerance for sinlge precision tests of matrix_solve_ls (and tighten it for double precision).
PiperOrigin-RevId: 165750936
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Commit eebcc861a authored by Jianwei Xie<xiejw@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fixed the race condition between multi eval step increments.
PiperOrigin-RevId: 165750595
---
Commit bbc0b8471 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Go: Update generated wrapper functions for TensorFlow ops.
PiperOrigin-RevId: 165748384
---
Commit 65f87c967 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Change device string in RecvNodeDescriptor in VirtualScheduler from const
reference to const as the RecvNodeDescriptor (and cached_recv_nodes map)
outlives device string from the NodeDef.
PiperOrigin-RevId: 165748244
---
Commit 57b0276cf authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Update ops-related pbtxt files.
PiperOrigin-RevId: 165747467
---
Commit 64e54423b authored by Derek Murray<mrry@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[tf.contrib.data] Fix nested dictionary handling in dataset elements.
Backports recent changes to the core version of the nest.py library.
Fixes #12372.
PiperOrigin-RevId: 165746517
---
Commit 378463ae8 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Make tf.eye accept Python integer shapes and avoid generating unnecessary shape handling ops.
Clean up test and add tests with placeholders.
PiperOrigin-RevId: 165746090
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Commit 109ecf823 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Add support for complex in matrix_solve_ls_op.
Split into separate files for each data type to speed up build.
PiperOrigin-RevId: 165744539
---
Commit 51441302d authored by Alexandre Passos<apassos@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Internal change.
PiperOrigin-RevId: 165737455
---
Commit d0cb32c2a authored by Alexandre Passos<apassos@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Docstring for ResourceVariable.
PiperOrigin-RevId: 165735441
---
Commit 32f4c5b6e authored by Chris Leary<leary@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[XLA] Add IsFinite op in tf2xla.
PiperOrigin-RevId: 165734702
---
Commit 5f5c3eb0a authored by Mark Daoust<markdaoust@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Move "supervisor.md" from programmer's guide to api_guides.
PiperOrigin-RevId: 165732026
---
Commit d001b58de authored by Derek Murray<mrry@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[tf.contrib.data] Fix handling of multi-output tf.py_func() in Dataset.map().
If the `map_func` returns a list of tensors, the current code will
attempt to stack it into a single tensor and raise an unintuitive
error. Some multi-output ops (such as `tf.py_func()`) return lists of
typically-not-stackable tensors. This change treats lists returned
from `map_func` as tuples; users who were relying on this
auto-stacking behavior should manually call `tf.stack()` (or
`tf.convert_to_tensor()`) on the list being returned.
Fixes #12396.
PiperOrigin-RevId: 165731970
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Commit e6c60fb36 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fix flakyness, sometimes the op takes ms to run.
PiperOrigin-RevId: 165728705
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Commit 360bff8ae authored by Ali Yahya<alive@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Makes tape.watch() work with ResourceVariables.
To this end, also adds a property, `device`, to TensorNode.
PiperOrigin-RevId: 165726368
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Commit 80bd004cd authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Implements SVDF model for keyword spotting tutorial.
PiperOrigin-RevId: 165725938
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Commit aaabf6b90 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fix bug: Using a ComputationDataHandle from the wrong ComputationBuilder.
PiperOrigin-RevId: 165724017
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Commit 107d165d9 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Use 2-arg TraceMe constructor to prevent unnecessary StrCat computation when
tracing is disabled.
PiperOrigin-RevId: 165722280
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Commit 7d01f89cc authored by Pete Warden<petewarden@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Android demo app for speech recognition
PiperOrigin-RevId: 165714459
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Commit a6729325a authored by Alexandre Passos<apassos@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Deletes convert_n_to_eager_tensor. Moves convert_to_eager_tensor to constant_op.
PiperOrigin-RevId: 165704074
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Commit 573b303ac authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
BUILD cleanup in tensorflow/core/kernels
PiperOrigin-RevId: 165688864
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Commit 711be6adc authored by Derek Murray<mrry@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
`Dataset.from_generator()` constructs a dataset from a Python generator.
With this change, it becomes possible to use a Python generator as the source
dataset for a `tf.contrib.data` input pipeline. This enables easier integration
with non-TensorFlow data sources. The generator can yield a nested structure of
NumPy arrays, or values convertible to NumPy arrays.
This addresses a concern raised in issue #7951.
PiperOrigin-RevId: 165663857
---
Commit 00594ecdd authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
New landing page and leftnav for Programmer's Guide.
PiperOrigin-RevId: 165660897
---
Commit 7359fec79 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Implement Batchnorm Inference by expanding them into smaller ops.
1. Add batch norm inference support in batchnorm_rewriter
2. Connect xla's batchnorm inference to tf's FusedBatchNorm
RELNOTES: n/a
PiperOrigin-RevId: 165655351
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Commit f0da8bf56 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[Rematerialization] Reconsider to remat operations with control dependencies
We added a conservartive logic to not rematerialize operations with control dependencies since the rematerialized operations could result in undesired ordering. However, we now realize that when we remat an operation, we also copy the dependencies of them, which guarantees the rematerialized operation has the same constraint as the original operation.
PiperOrigin-RevId: 165654629
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Commit a1225879c authored by Chris Leary<leary@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[XLA] Propagate error code in computation replay tool.
PiperOrigin-RevId: 165654497
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Commit 513def0bb authored by Benoit Steiner<bsteiner@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fixed BuildOpInfoWithoutDevice
PiperOrigin-RevId: 165653933
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Commit d7e425f0b authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fix linear algebra benchmarks.
PiperOrigin-RevId: 165653891
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Commit 465c40819 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fix the shape information propagation for Enter op.
PiperOrigin-RevId: 165653579
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Commit c0198fd8d authored by Derek Murray<derek.murray@gmail.com>
Committed by gunan<gunan@google.com>:
[CMake] Add missing dependencies on boosted_trees protos and other fixes (#12315)
* [CMake] Add missing dependencies
* Avoid rebuilding boosted_trees protos for Python.
* Add GPU implementation ZeroInitializerOp to the CMake build.
---
Commit 641943fd7 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Update ops-related pbtxt files.
PiperOrigin-RevId: 165652758
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Commit e31346452 authored by Jonathan Hseu<jhseu@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
TPUEstimator: Fix the outfeed thread join.
PiperOrigin-RevId: 165651781
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Commit 565a9d350 authored by Vijay Vasudevan<vrv@google.com>
Committed by Andrew Harp<andrewharp@users.noreply.github.com>:
Add missing 'type' keyword to ArgumentParser add_argument (#12275)
Fixes #12210
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Commit 19a55725a authored by Rohan Jain<rohanj@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Allowing functions to run across devices. This change expands the ProcessFunctionLibraryRuntime library to Instantiate and Run functions on different devices. When a FunctionLibraryRuntime encounters a function with a target that is another device, it delegates Instantiate() and Run() calls to the ProcessFunctionLibraryRuntime.
This change also moves the table_ containing all function instantiations to the PFLR instead of the FunctionLibraryRuntime.
PiperOrigin-RevId: 165651194
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Commit 8c0853db7 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Add a test for negative and zero pow() input.
PiperOrigin-RevId: 165650096
---
Commit a3c4e980e authored by Pete Warden<petewarden@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fixed input shape for freezing audio graphs
PiperOrigin-RevId: 165649546
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Commit 9b9e5989d authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Add a call_logit_fn utility for logit_fn's, similar to Estimator's _call_model_fn.
PiperOrigin-RevId: 165649388
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Commit 4ff1f4442 authored by Amit Patankar<amitpatankar@google.com>
Committed by Amit Patankar<amitpatankar@google.com>:
Remove the script as well if building tf_nightly.
---
Commit 373d78987 authored by Amit Patankar<amitpatankar@google.com>
Committed by Amit Patankar<amitpatankar@google.com>:
Adding the break.
---
Commit 0139ac983 authored by Amit Patankar<amitpatankar@google.com>
Committed by Amit Patankar<amitpatankar@google.com>:
Remove tensorboard as a required package if we are building tf_nightly.
---
Commit a92bd5d5c authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
BEGIN_PUBLIC
Automated g4 rollback of changelist 165630063
PiperOrigin-RevId: 165957821
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Remove macro reverted in #12219.
PiperOrigin-RevId: 165362077
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Commit 9f81374c3 authored by raymondxyang<zihao.yang@microsoft.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
Add option for build more python tests in Cmake (#11853)
* Ignore Windows built project
* Fix deprecated methods in tf.contrib.python
* Fix regex match for Windows build in contrib.keras
* Fix Regex match for Windows build in session_bundle
* * Fix deprecated methods
* Fix regex match for Windows
* Fix compatibility issue with Python 3.x
* Add missing ops into Windows build for test
* Enabled more testcases for Windows build
* Clean code and fix typo
* Add conditional cmake mode for enabling more unit testcase
* Add Cmake mode for major Contrib packages
* Add supplementary info in RAEDME for new cmake option
* * Update tf_tests after testing with TF 1.3
* Clean code and resolve conflicts
* Fix unsafe regex matches and format code
* Update exclude list after testing with latest master branch
* Fix missing module
---
Commit 98f0e1efe authored by Yong Tang<yong.tang.github@outlook.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
Dynamic ksize and strides with MaxPool (#11875)
* Dynamic ksize with max_pool
This fix tries to fix the issue raised in 4746 where ksize
is static (attr) with max_pool.
This fix changes ksize to input tensor so that it is dynamic now.
This fix fixes 4746.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
* Add dynamic ksize to MaxPoolGrad and MaxPoolGradGrad
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
* Add test cases for max_pool_v2
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
* Fix GPU Jenkins issue.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
* Enable MaxPoolV2 in GPU
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
* Hide MaxPoolV2 and other fixes.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
---
Commit 02d6bc185 authored by Bairen Yi<byronyi@users.noreply.github.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
remove useless variable (#12212)
---
Commit ed6b0d905 authored by namrata-ibm<bhavenamrata@gmail.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
Adding support for s390x in calculation of cpu_frequency (#12201)
---
Commit 627dfc9dd authored by Taehoon Lee<taehoonlee@snu.ac.kr>
Committed by Taehoon Lee<taehoonlee@snu.ac.kr>:
Fix typos
---
Commit c0f9b0a91 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
In fast-math mode emit a tanh that has a faster min/max.
PiperOrigin-RevId: 164943597
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Commit 87605f3d6 authored by Kay Zhu<kayzhu@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[TF:XLA] Use HloEvaluator for ComputeConstant, remove the need of a dedicated
compute constant backend.
PiperOrigin-RevId: 164940970
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Commit 881de45c2 authored by Taehoon Lee<me@taehoonlee.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
Add bool type supports for GPU kernels (#11927)
* Add bool type supports for GPU kernels
* Add bool type test codes for GPU kernels
---
Commit eeacdcdb1 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Add missing "CPU" suffix in registrations.
PiperOrigin-RevId: 164939527
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Commit de01be952 authored by namrata-ibm<bhavenamrata@gmail.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
Adding support for Big Endian in graph_constructor_test and wav_io (#12179)
---
Commit 26719d29f authored by QingYing Chen<pkudysj@126.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
Implement CRF decode (Viterbi decode) for tensor (#12056)
* Implement CRF decoding for tensors
* add test code for tensor version's CRF decoding
* made modifications according to pylint
* add some comments for crf decode
* remove useless code
* add comments at the top comment of crf module and add more comments in crf_test
* capitalize first char of first word in comments
* replace crf_decode test code with a deterministic example
---
Commit f9a81ca2f authored by Pete Warden<pete@petewarden.com>
Committed by gunan<gunan@google.com>:
Create CI build script for Raspberry Pi (#12190)
* Create CI build script for Raspberry Pi
* Moved location of Pi build script
---
Commit e2a163a90 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Merge code from PR #11940 with internal changes from cl/164796436, and update Python tests to also run on GPU.
PiperOrigin-RevId: 164929133
---
Commit 08bbfa187 authored by Taehoon Lee<me@taehoonlee.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
Fix typos (#12195)
---
Commit ab96f41fb authored by Luke Iwanski<luke@codeplay.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
[OpenCL] Extends matmul_benchmark.py to cover SYCL (#11697)
* [OpenCL] Extends matmul_benchmark.py to cover SYCL
* Fixed typo
* /gpu:0 -> /device:GPU:0
* Fixes control_flow_ops_py_test
* /gpu: -> /device:GPU:
* Fixes //tensorflow/python/profiler/internal:run_metadata_test
* gpu: -> GPU:
* Fixes tfprof_node
* [OpenCL] Fixes device path to name with many colons (#123)
The device path is constructed from a device name by replacing all
colons with underscores. Some device names contain more than one colon,
for example 'device:SYCL:0' which gives a path 'device_SYCL_0'. The
previous code would not convert this back to the original device name,
but rather to 'device:SYCL_0'.
An alternative fix would be to convert all underscores to colons in the
device name (i.e. remove the restriction inside `replace("_", ":", 1)`),
however I'm not sure if there are any device names which contain
underscores.
* If no gpu device aviable fake one
* gpu: -> device:GPU
* Fixes profiler test
* /gpu:x -> /device:GPU:x
* Fixes debug_io_utils_test.cc test
* Fixes device_name_utils_test.cc
---
Commit 35e7a3665 authored by Yong Tang<yong.tang.github@outlook.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
Remove unneeded casting of int64 for reverse_sequence (#12192)
This fix remove unneeded cast of int64 for reverse_sequence:
```
lengths = math_ops.to_int64(lengths)
```
as int32 has already been enabled for reverse_sequence.
Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
---
Commit 9fba8c185 authored by Anna R<annarev@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Add benchmark dashboard link to benchmarks doc. Also, I added a link and
description for Benchmarks page to Community index page.
PiperOrigin-RevId: 164924906
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Commit bb6f32fa7 authored by Mark Heffernan<meheff@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Make HloAliasAnalysis updatable after changes to the HLO graph.
As part of this change make HloAliasAnalysis a thinner layer which
basically only holds a map from HloValue to HloBuffer and vice versa.
PiperOrigin-RevId: 164923041
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Commit 9103096c1 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by Thomas K?ppe<tkoeppe@google.com>:
Merged commit includes the following changes:
164923041 by meheff:
Make HloAliasAnalysis updatable after changes to the HLO graph.
As part of this change make HloAliasAnalysis a thinner layer which
basically only holds a map from HloValue to HloBuffer and vice versa.
--
PiperOrigin-RevId: 164923041
---
Commit 822603aed authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Merging sibling fusion instruction using multi_output_fusion
PiperOrigin-RevId: 164920220
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Commit c035aa2a8 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Go: Update generated wrapper functions for TensorFlow ops.
PiperOrigin-RevId: 164917891
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Commit e1e81d9ba authored by Luke Iwanski<luke@codeplay.com>
Committed by Rasmus Munk Larsen<rmlarsen@google.com>:
[OpenCL] Fixes double memcpy bug (#151) (#12173)
* [OpenCL] Fixes double memcpy bug (#151)
As the debg CopyOp is called on a Tensor without type, we need to use
the DataType enum to get type information, and use this to pass the type
on to Eigen. This is a workaround Eigen's need to have a type when
calling memcpy. If the Eigen memcpy can be provided without a type
requirement, then the memcpy in sycl_util is unnecessary.
* Acts on feedback from: #12173/files/32cb12a9001b672425867b5a3110fd98e737a20b#r132496277
---
Commit d9ca2d86d authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Internal change
PiperOrigin-RevId: 164916465
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Commit b8d13d218 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Remove more parts of DCASGD missed in the first pass. (47949b)
PiperOrigin-RevId: 164914552
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Commit 73b3d52c7 authored by Alexandre Passos<apassos@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
cmake fix
PiperOrigin-RevId: 164911656
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Commit 2173b5b0a authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Allow TFE_TensorHandleCopyToDevice to have the same device as src and
destination. It will reuse the same underlying buffer in those cases.
PiperOrigin-RevId: 164909906
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Commit 13eb3b90e authored by Alexandre Passos<apassos@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Experimental C and Python APIs to invoke TensorFlow kernels on concrete values.
PiperOrigin-RevId: 164902588
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Commit 7dfabcc01 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Initialize ExecutionOptions in ComputeConstant to default values.
PiperOrigin-RevId: 164894867
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Commit c8897e9bc authored by Benoit Steiner<bsteiner@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Static required time computation
PiperOrigin-RevId: 164894645
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Commit 076158f9b authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Enable implicit->explicit conversion by default.
PiperOrigin-RevId: 164890915
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Commit 58c4a4cb1 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Bugfix: number of input channels is not necessarily in the last dimension, after introduction of data_format param.
PiperOrigin-RevId: 164889729
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Commit 8f9b1af8a authored by Igor Saprykin<isaprykin@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Recover MonitoredSession when the Coordinator is requested to stop with one of the _PREEMPTION_ERRORS.
When SyncReplicasOptimizer is used, a preemption in the Coordinator may result in two cases:
Case 1) the session gets silently marked as complete
Case 2) the session gets stuck
This CL aims to solve and verify solutions for both of these problems. Fix 1 changes the should_stop logic. Fix 2 changes the CoordinatedSession.run() logic.
SyncReplicasOptimizer runs a separate set of threads using a Coordinator instance. Those threads do FIFOQueue.enqueue; the main thread does a blocking FIFOQueue.dequeue.
`sync_token_q` FIFOQueue is on parameter-servers. When one of the PS instances gets preempted, an AbortedError causes the Coordinator to stop via request_stop(ex). That by itself changes the state of MonitoredSession.should_stop() to True (Fix 1).
Results of the blocking Dequeue operation are sent to the chief worker via Recv. What happens next depends on the amount of tokens in `sync_token_q`. If there are enough for the next call to Dequeue to return, then the low-level "tf session run() call" returns. The next iteration of the `while not MonitoredSession.should_stop()` loop decides that the training is complete (Case 1).
If there are not enough tokens in `sync_token_q`, then the blocking Dequeue is going to keep waiting for them. This results in the graph execution getting stuck and the whole session getting garbage collected after 10 minutes (Case 2).
We decided to fix that by re-creating a session after it gets garbage collected (Fix 2). An alternative was to try to cancel the pending Dequeue operation, but it's not clear that it is the right thing to do and it is also not easy.
PiperOrigin-RevId: 164888390
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Commit 46e4de6e5 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Undo loop fusion changes for now as they seem to be altering a few results.
END_PUBLIC
RELNOTES: n/a
BEGIN_PUBLIC
BEGIN_PUBLIC
Automated g4 rollback of changelist 164825735
PiperOrigin-RevId: 165340331
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Bairen Yi
A. Unique TensorFlower
Yong Tang
cosine0
Mingxing Tan
Derek Murray
Martin Wicke
Ankur Taly
Jeremy Lau
Eugene Brevdo
Shanqing Cai
Andrew Harp