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  /external/tensorflow/tensorflow/contrib/nn/python/ops/
sampling_ops.py 40 and j ranges over the rows of `inputs`. For efficiency, we rearrange the
  /external/tensorflow/tensorflow/core/kernels/
adjust_contrast_op.cc 275 // use their flattened structure to gain vectorinization efficiency.
sparse_conditional_accumulator.h 362 // be fixed if it affects efficiency.
  /external/tensorflow/tensorflow/docs_src/performance/
quantization.md 12 That means pure inference efficiency has become a burning issue for a lot of
  /external/tensorflow/tensorflow/python/keras/_impl/keras/preprocessing/
text.py 198 or a generator of strings (for memory-efficiency)
  /frameworks/av/media/libstagefright/codecs/amrnb/dec/src/
lsp_avg.h 109 Word16 lsp_meanSave[M]; /* Averaged LSPs saved for efficiency */
  /frameworks/base/core/java/android/webkit/
WebViewFactory.java 60 // Cache the factory both for efficiency, and ensure any one process gets all webviews from the
  /frameworks/base/media/java/android/media/
ThumbnailUtils.java 72 * size. If not, then it'll create a thumbnail from original image. Due to efficiency
  /libcore/luni/src/main/java/org/xml/sax/helpers/
XMLReaderAdapter.java 42 * property, that will also be used to improve efficiency.</p>
  /libcore/ojluni/src/main/java/java/util/
AbstractCollection.java 423 * efficiency.
  /packages/apps/Gallery2/src/com/android/gallery3d/glrenderer/
NinePatchTexture.java 182 // (width, height). We pre-compute the coordinates for efficiency.
  /prebuilts/gcc/linux-x86/host/x86_64-linux-glibc2.15-4.8/x86_64-linux/include/c++/4.8/bits/
valarray_before.h 60 // 2) efficiency -- object functions can be easily inlined
  /prebuilts/gcc/linux-x86/host/x86_64-w64-mingw32-4.8/x86_64-w64-mingw32/include/c++/4.8.3/bits/
valarray_before.h 60 // 2) efficiency -- object functions can be easily inlined
  /prebuilts/gdb/darwin-x86/lib/python2.7/wsgiref/
handlers.py 332 just separates write and flush operations for greater efficiency
  /prebuilts/gdb/linux-x86/lib/python2.7/wsgiref/
handlers.py 332 just separates write and flush operations for greater efficiency
  /prebuilts/go/darwin-x86/doc/codewalk/
markov.xml 114 <code>Readers</code>. For efficiency we wrap the provided
  /prebuilts/go/darwin-x86/src/runtime/
HACKING.md 30 sharded for efficiency, but doesn't need to be per-thread or
  /prebuilts/go/linux-x86/doc/codewalk/
markov.xml 114 <code>Readers</code>. For efficiency we wrap the provided
  /prebuilts/go/linux-x86/src/runtime/
HACKING.md 30 sharded for efficiency, but doesn't need to be per-thread or
  /prebuilts/python/darwin-x86/2.7.5/lib/python2.7/wsgiref/
handlers.py 332 just separates write and flush operations for greater efficiency
  /prebuilts/python/linux-x86/2.7.5/lib/python2.7/site-packages/setools/
infoflow.py 287 # included in this main graph: memory is traded off for efficiency
  /prebuilts/python/linux-x86/2.7.5/lib/python2.7/wsgiref/
handlers.py 332 just separates write and flush operations for greater efficiency
  /system/core/liblog/
logger_write.c 180 * choose a mitigation stance for efficiency instead of incuring the cost
  /toolchain/binutils/binutils-2.27/bfd/
coff-mcore.c 160 entry, we'll get some runtime efficiency back]. Note that this
elf32-mcore.c 209 entry, we'll get some runtime efficiency back]. Note that this

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