From 7012eb5fac6fff661e80a6c3172421f87e8849b9 Mon Sep 17 00:00:00 2001 From: Geor Kasapidi Date: Fri, 24 Feb 2023 14:05:40 +0200 Subject: [PATCH] update readme --- README.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 7c85893..0737713 100644 --- a/README.md +++ b/README.md @@ -53,9 +53,9 @@ let graph = try OnnxGraph( ### 1) Raw inputs/outputs: ``` swift -let outputs: [MPSGraphTensorData] = graph.encode( - to: , - inputs: <[String: MPSGraphTensorData]> // String key is a model corresponding input name +let outputs: [MPSGraphTensorData] = graph( + <[String: MPSGraphTensorData]> // String key is a model corresponding input name + in: ) ``` @@ -66,7 +66,7 @@ This method requires manual data transformation from/to MPSGraphTensorData. For ``` swift let input: MPSGraphTensorData = .NCHW( texture: , - tensor: , + matching: , in: ) ``` @@ -75,7 +75,7 @@ let input: MPSGraphTensorData = .NCHW( ``` swift let image: MPSTemporaryImage = - .transposeNHWC(in: ) + .nhwc(in: ) .temporaryImage(in: ) ``` @@ -104,7 +104,7 @@ let texture: MTLTexture = graph.texture2DFrom( # MPSGraph DSL -In addition to ONNX graphs, MPSX provides a convenient API for building [custom computational graphs](/Sources/MPSXTests/FoundationTests.swift#L16) similar to NumPy. +In addition to ONNX graphs, MPSX provides a convenient API for building [custom computational graphs](/Sources/MPSXTests/FoundationTests.swift#L16) similar to NumPy/PyTorch. # Links @@ -127,7 +127,7 @@ done; MPSX... 1) supports limited set of ONNX operators -2) is Pytorch oriented - TF models converted to ONNX may not be supported +2) is PyTorch oriented - TF models converted to ONNX may not be supported 3) is available only on iOS 15+/macOS 12+ # Installation