AdjustContrast
kernel deprecated, new kernelAdjustContrastv2
takes and outputs float only.adjust_contrast
now takes all data types.adjust_brightness
'sdelta
argument is now always assumed to be in[0,1]
(as is the norm for images in floating point formats), independent of the data type of the input image.- The image processing ops do not take
min
andmax
inputs any more, casting safety is handled bysaturate_cast
, which makes sure over- and underflows are handled before casting to data types with smaller ranges. - For C++ API users:
IsLegacyScalar
andIsLegacyVector
are now gone fromTensorShapeUtils
since TensorFlow is scalar strict within Google (for example, the shape argument totf.reshape
can't be a scalar anymore). The open source release was already scalar strict, so outside GoogleIsScalar
andIsVector
are exact replacements. - The following files are being removed from
tensorflow/core/public/
:env.h
->../platform/env.h
status.h
->../lib/core/status.h
tensor.h
->../framework/tensor.h
tensor_shape.h
->../framework/tensor_shape.h
partial_tensor_shape.h
->../framework/partial_tensor_shape.h
tensorflow_server.h
deleted
- For C++ API users:
TensorShape::ShortDebugString
has been renamed toDebugString
, and the previousDebugString
behavior is gone (it was needlessly verbose and produced a confusing empty string for scalars). GraphOptions.skip_common_subexpression_elimination
has been removed. All graph optimizer options are now specified viaGraphOptions.OptimizerOptions
.- ASSERT_OK / EXPECT_OK macros conflicted with external projects, so they were renamed TF_ASSERT_OK, TF_EXPECT_OK. The existing macros are currently maintained for short-term compatibility but will be removed.
- The Python API will now properly set the
list
member ofAttrValue
in constructedGraphDef
messages for empty lists. The serialization of some graphs will change, but the change is both forwards and backwards compatible. It will break tests that compare a generatedGraphDef
to a golden serializedGraphDef
.
-
Python 3.3+ support via changes to python codebase and ability to specify python version via ./configure.
-
Some improvements to GPU performance and memory usage: convnet benchmarks roughly equivalent with native cudnn v2 performance. Improvements mostly due to moving to 32-bit indices, faster shuffling kernels. More improvements to come in later releases.
-
Lots of fixes to documentation and tutorials, many contributed by the public.
-
271 closed issues on github issues.
- tf.nn.fixed_unigram_candidate_sampler changed its default 'distortion' attribute from 0.0 to 1.0. This was a bug in the original release that is now fixed.
Initial release of TensorFlow.