提交 b9a40e4c authored 作者: notoraptor's avatar notoraptor

Update `Vision State`.

上级 d1039d20
...@@ -165,11 +165,13 @@ Note: There is no short term plan to support multi-node computation. ...@@ -165,11 +165,13 @@ Note: There is no short term plan to support multi-node computation.
Theano Vision State Theano Vision State
=================== ===================
Here is the state of that vision as of January 24th, 2017 (after Theano 0.9.0beta1): Here is the state of that vision as of February 15th, 2017 (after Theano 0.9.0rc1):
* We support tensors using the `numpy.ndarray` object and we support many operations on them. * We support tensors using the `numpy.ndarray` object and we support many operations on them.
* We support sparse types by using the `scipy.{csc,csr,bsr}_matrix` object and support some operations on them. * We support sparse types by using the `scipy.{csc,csr,bsr}_matrix` object and support some operations on them.
* We have implementing/wrapping more advanced linear algebra operations. Still many more possible. * We have implementing/wrapping more advanced linear algebra operations. Still many more possible.
* We support the creation of new operations from graphs at runtime, which allow gradient overload for every input
and inlining at the start of compilation.
* We have many graph transformations that cover the 4 categories listed above. * We have many graph transformations that cover the 4 categories listed above.
* We can improve the graph transformation with better storage optimization * We can improve the graph transformation with better storage optimization
and instruction selection. and instruction selection.
...@@ -195,7 +197,9 @@ Here is the state of that vision as of January 24th, 2017 (after Theano 0.9.0bet ...@@ -195,7 +197,9 @@ Here is the state of that vision as of January 24th, 2017 (after Theano 0.9.0bet
* No multi-node support. * No multi-node support.
* Most, but not all NumPy functions/aliases are implemented. * Most, but not all NumPy functions/aliases are implemented.
* https://github.com/Theano/Theano/issues/1080 * https://github.com/Theano/Theano/issues/1080
* Wrapping an existing Python function in easy and documented. * Wrapping an existing Python function in easy and documented.
* We know how to separate the shared variable memory * We know how to separate the shared variable memory
storage location from its object type (tensor, sparse, dtype, broadcast storage location from its object type (tensor, sparse, dtype, broadcast
......
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