- Added several fixed-sized arrow markers for reference edges (small, medium, large, xlarge)
- Added a method to shorten the path enough such that the tip of the start/end marker will
  point to the start/end of the path. It needs an arbitrary marker.
- Updated the legend to reflect that only ref edges have an arrow.
- Removed unused css related to this.
Change: 118530630

Change: 118522346

Also fix some warnings about unsafe conversions.
Change: 118519927

Add a test that we actually check for array length (we were not.)
Change: 118518452

// OLD
Benchmark                             Time(ns)    CPU(ns) Iterations
--------------------------------------------------------------------
BM_ConvFloatDepthwiseBkInCPU1_conv0  207770233  207338129        100  796.0M items/s 32_112_112_3_8_24_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv1  715403538  713939287        100  616.4M items/s 32_112_112_64_1_64_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv2  357349749  356594057        100  617.0M items/s 32_56_56_128_1_128_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv3  274697435  274160117        100  802.7M items/s 32_56_56_128_1_128_3_3_2_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv4   87072020   86874244        100  633.1M items/s 32_28_28_128_1_128_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv5   87172482   86948501        100  632.4M items/s 32_14_14_512_1_512_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv6   46763611   46620163        100  589.4M items/s 32_7_7_1024_1_1024_3_3_1_2_cpu1

// NEW 1-thread
Benchmark                             Time(ns)    CPU(ns) Iterations
--------------------------------------------------------------------
BM_ConvFloatDepthwiseBkInCPU1_conv0   60173061   59839526        100  2.7G items/s 32_112_112_3_8_24_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv1   99396102   99143542        100  4.3G items/s 32_112_112_64_1_64_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv2   39376616   39226953        100  5.5G items/s 32_56_56_128_1_128_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv3   35987577   35843443        100  6.0G items/s 32_56_56_128_1_128_3_3_2_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv4    9665813    9600518        100  5.6G items/s 32_28_28_128_1_128_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv5   12498989   12427035        100  4.3G items/s 32_14_14_512_1_512_3_3_1_2_cpu1
BM_ConvFloatDepthwiseBkInCPU1_conv6    8459759    8397047        100  3.2G items/s 32_7_7_1024_1_1024_3_3_1_2_cpu1

// NEW 4-threads
Benchmark                             Time(ns)    CPU(ns) Iterations
--------------------------------------------------------------------
BM_ConvFloatDepthwiseBkInCPU4_conv0   30696635  101663830        100  5.3G items/s 32_112_112_3_8_24_3_3_1_2_cpu4
BM_ConvFloatDepthwiseBkInCPU4_conv1   68884630  198616710        100  6.3G items/s 32_112_112_64_1_64_3_3_1_2_cpu4
BM_ConvFloatDepthwiseBkInCPU4_conv2   16948037   50360587        100  12.7G items/s 32_56_56_128_1_128_3_3_1_2_cpu4
BM_ConvFloatDepthwiseBkInCPU4_conv3   15834408   46873689        100  13.6G items/s 32_56_56_128_1_128_3_3_2_2_cpu4
BM_ConvFloatDepthwiseBkInCPU4_conv4    3904734   11659079        167  13.8G items/s 32_28_28_128_1_128_3_3_1_2_cpu4
BM_ConvFloatDepthwiseBkInCPU4_conv5    3482083   12555105        188  15.5G items/s 32_14_14_512_1_512_3_3_1_2_cpu4
BM_ConvFloatDepthwiseBkInCPU4_conv6    2330680    8593020        281  11.5G items/s 32_7_7_1024_1_1024_3_3_1_2_cpu4
Change: 118514706

instead of 48 (on my machine).
Change: 118512022

gradients by 1 to 10% depending on the size of the convolution kernel.
Change: 118505660

Change: 118497433

- Change the stride, and in_stride template arguments of Eigen
  SpatialConvolution, SpatialConvolutionBackwardInput, and
  SpatialConvolutionBackwardKernel to row_stride, col_stride, row_in_stride,
  col_in_stride.

- Change tensorflow kernels to pass the additional stride parameters.

- Rationalize the place where we swap row/col: swap just before calling Eigen.

This just enables the plumbing. Non-square strides are still forbidden in the ops.
Change: 118484322

Parse uploaded pbtxt in chunks to allow for loading of large pbtxt files, this only affects files uploaded with the file chooser menu not XHR requests.
Change: 118479897

having the ops explicitly return a failure that they can't handle
overly-large inputs).  Most of these should never affect correct
tf programs until people get a lot more memory in their machines.
Change: 118476613

float and int for all types T. (The assumption doesn't hold for Eigen::half.)

These were all ops I could find in CPU implementation; probably, some remain
for GPU (and some other problems remain before we can turn on Eigen::half for
all of them).
Change: 118464463

Adds a Timeline class which can convert a StepStats protobuf into
a JSON-formatted trace.  This trace can be loaded into any Chrome
web browser via the chrome://tracing URL.
Change: 118461709

Change: 118445579

Change: 118445207

implicitly convertible from bool (like Eigen::half).

Note: This does not enable half support for ReluOp in itself, although it is
an important step of the way.
Change: 118444029

Change: 118427688

Change: 118414827

Change: 118414762

Change: 118414301

Moved the higher order functions into functional_ops.py, to avoid some potential circular dependency.
Change: 118412058

Change: 118410742

Change: 118409321

for Eigen.
Change: 118408303

is_initialized is safe.
Change: 118405243

This moves the "Other..." documentation of make_all from tf.image to
tf.contrib.layers, since tf.contrib.layers has no __all__ and thus leaks all
sorts of random things.
Change: 118403996

This change accounts for the fact that the `RequestCancelled` callback
will still be called after a `RequestReceived(ok = false)` callback.

In refactoring this code, this change also adds the ability for
enqueued requests to enable cancellation selectively, which reduces
the allocation count of completion queue tags for client-side
cancellation that serve no useful purpose. Only methods that have a
server-side implementation of cancellation should register a
cancellation tag.
Change: 118403144

Change: 118401805

Change: 118401706

Change: 118401267

Change: 118397198

collection list.  The previous behavior was to return the list
itself: If other items were later added to the collection the
list returned initially would show them.

Add get_collection_ref() to return the collection list itself.
Change: 118396574

Change: 118393590

Build android_tensorflow_lib_lite with -Os to reduce the size of libandroid_tensorflow_lib.so. Kernel code in android_tensorflow_lib is still built with -O2 for performance reasons.
Change: 118389861

be built depending on these rules. Otherwise the ops and some other components
are dropped because there are no link-time references to them.

This change has no effect on .so files needed by normal Android NDK Java apps.
Change: 118387009

instead of the filename.

Change FindKernelDef to also return the class name, to help a tool that
generates ops_to_register.h to find the set of class names.
Change: 118381472

Change: 118376780

Change: 118376252

Change: 118375255

Bring back fast_cpp_protos bazel configuration and remove 64MB limit of protobufs. This speeds-up graph serialization by ~15x for users building TensorFlow from source.

Note that you can now install a faster pip binary for protobuf using the instructions
in https://github.com/tensorflow/tensorflow/commit/8ac009728db931ef3119a337bd23250c89bc7efe

This only affects building and running from within the bazel environment.
Change: 118374862