Not a research project.

Follows tensorflow@68d19b9.
shadaj · Jul 25, 2018 · eeef0c7 · eeef0c7
1 parent 899884b
commit eeef0c7
Show file tree

Hide file tree

Showing 2 changed files with 2 additions and 2 deletions.
diff --git a/Installation.md b/Installation.md
@@ -4,7 +4,7 @@ To install Swift for TensorFlow, download one of the packages below and follow t
 
 **Note:** If you want to modify the Swift for TensorFlow source code or build with a custom version of TensorFlow, see [here](https://github.com/apple/swift/blob/tensorflow/README.md) for instructions on building from source.
 
-**Note:** Swift for TensorFlow is an early stage research project. It has been released to enable open source development and is not yet ready for general use by machine learning developers.
+**Note:** Swift for TensorFlow is an early stage project. It has been released to enable open source development and is not yet ready for general use by machine learning developers.
 
 ## Pre-built Packages
 

diff --git a/docs/GraphProgramExtraction.md b/docs/GraphProgramExtraction.md
@@ -545,4 +545,4 @@ Our user model fits in a single paragraph: you write normal imperative Swift cod
 
 One of the beauties of this user model is that directly aligns with several of the defaults encouraged by the Swift language (e.g. closures default to non-escaping and the use of zero-cost abstractions to build high level APIs), and the core values of Swift API design (e.g. the pervasive use of value semantics strongly encourages the use of structs over classes).  We believe that this will make Swift for TensorFlow "feel nice in practice" because you don’t have to resort to anti-idiomatic design to get things to work.
 
-Our implementation work is still early, but we are shifting from an early research project into a public open source project now because we believe that the theory behind this approach has been proven out.  We are far enough along in the implementation to have a good understanding of the engineering concerns facing an actual implementation of these algorithms.
+Our implementation work is still early, but we are shifting from an early stage project into a public open source project now because we believe that the theory behind this approach has been proven out.  We are far enough along in the implementation to have a good understanding of the engineering concerns facing an actual implementation of these algorithms.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -545,4 +545,4 @@ Our user model fits in a single paragraph: you write normal imperative Swift cod

		One of the beauties of this user model is that directly aligns with several of the defaults encouraged by the Swift language (e.g. closures default to non-escaping and the use of zero-cost abstractions to build high level APIs), and the core values of Swift API design (e.g. the pervasive use of value semantics strongly encourages the use of structs over classes). We believe that this will make Swift for TensorFlow "feel nice in practice" because you don’t have to resort to anti-idiomatic design to get things to work.

		Our implementation work is still early, but we are shifting from an early research project into a public open source project now because we believe that the theory behind this approach has been proven out. We are far enough along in the implementation to have a good understanding of the engineering concerns facing an actual implementation of these algorithms.
		Our implementation work is still early, but we are shifting from an early stage project into a public open source project now because we believe that the theory behind this approach has been proven out. We are far enough along in the implementation to have a good understanding of the engineering concerns facing an actual implementation of these algorithms.