From ddea0a855e474865eb73d7267abc22e8352ab26e Mon Sep 17 00:00:00 2001
From: Ningxin Hu <ningxin.hu@intel.com>
Date: Sun, 18 Feb 2024 15:57:28 +0800
Subject: [PATCH] Update code editor sample to the latst implementation

* Use MLGraphBuilder.constant(desc, value) for scalar
* Use `gemm` which supports 2Dx2D
* Use MLOperandDescriptor.dataType
* Remove optional output sample
---
 code/samples/matmul.js           |  6 +++---
 code/samples/mul_add.js          |  5 +++--
 code/samples/optional_outputs.js | 28 ----------------------------
 code/samples/simple_graph.js     |  2 +-
 code/samples_repo.js             |  1 -
 5 files changed, 7 insertions(+), 35 deletions(-)
 delete mode 100644 code/samples/optional_outputs.js

diff --git a/code/samples/matmul.js b/code/samples/matmul.js
index 20e9d906..03d54698 100644
--- a/code/samples/matmul.js
+++ b/code/samples/matmul.js
@@ -3,12 +3,12 @@ const context = await navigator.ml.createContext();
 // The following code multiplies matrix a [3, 4] with matrix b [4, 3]
 // into matrix c [3, 3].
 const builder = new MLGraphBuilder(context);
-const descA = {type: 'float32', dataType: 'float32', dimensions: [3, 4]};
+const descA = {dataType: 'float32', dimensions: [3, 4]};
 const a = builder.input('a', descA);
-const descB = {type: 'float32', dataType: 'float32', dimensions: [4, 3]};
+const descB = {dataType: 'float32', dimensions: [4, 3]};
 const bufferB = new Float32Array(sizeOfShape(descB.dimensions)).fill(0.5);
 const b = builder.constant(descB, bufferB);
-const c = builder.matmul(a, b);
+const c = builder.gemm(a, b);
 
 const graph = await builder.build({c});
 const bufferA = new Float32Array(sizeOfShape(descA.dimensions)).fill(0.5);
diff --git a/code/samples/mul_add.js b/code/samples/mul_add.js
index 08267de6..b4a6c564 100644
--- a/code/samples/mul_add.js
+++ b/code/samples/mul_add.js
@@ -1,8 +1,9 @@
-const operandType = {type: 'float32', dataType: 'float32', dimensions: [2, 2]};
+const operandType = {dataType: 'float32', dimensions: [2, 2]};
 const context = await navigator.ml.createContext();
 const builder = new MLGraphBuilder(context);
 // 1. Create a computational graph 'C = 0.2 * A + B'.
-const constant = builder.constant(0.2);
+const constant = builder.constant(
+    {dataType: 'float32'}, new Float32Array([0.2]));
 const A = builder.input('A', operandType);
 const B = builder.input('B', operandType);
 const C = builder.add(builder.mul(A, constant), B);
diff --git a/code/samples/optional_outputs.js b/code/samples/optional_outputs.js
deleted file mode 100644
index 4e3da239..00000000
--- a/code/samples/optional_outputs.js
+++ /dev/null
@@ -1,28 +0,0 @@
-const context = await navigator.ml.createContext();
-
-// Build a graph with two outputs.
-const builder = new MLGraphBuilder(context);
-const descA = {type: 'float32', dataType: 'float32', dimensions: [3, 4]};
-const a = builder.input('a', descA);
-const descB = {type: 'float32', dataType: 'float32', dimensions: [4, 3]};
-const bufferB = new Float32Array(sizeOfShape(descB.dimensions)).fill(0.5);
-const b = builder.constant(descB, bufferB);
-const descC = {type: 'float32', dataType: 'float32', dimensions: [3, 3]};
-const bufferC = new Float32Array(sizeOfShape(descC.dimensions)).fill(1);
-const c = builder.constant(descC, bufferC);
-const d = builder.matmul(a, b);
-const e = builder.add(d, c);
-const graph = await builder.build({'d': d, 'e': e});
-
-const bufferA = new Float32Array(sizeOfShape(descA.dimensions)).fill(0.5);
-const inputs = {'a': bufferA};
-
-// Compute d.
-const bufferD = new Float32Array(sizeOfShape([3, 3]));
-const resultsD = await context.compute(graph, inputs, {'d': bufferD});
-console.log(`values: ${resultsD.outputs.d}`);
-
-// Compute e.
-const bufferE = new Float32Array(sizeOfShape([3, 3]));
-const resultsE = await context.compute(graph, inputs, {'e': bufferE});
-console.log(`values: ${resultsE.outputs.e}`);
diff --git a/code/samples/simple_graph.js b/code/samples/simple_graph.js
index e5e480d5..ff03401e 100644
--- a/code/samples/simple_graph.js
+++ b/code/samples/simple_graph.js
@@ -18,7 +18,7 @@ const TENSOR_SIZE = 8;
 const builder = new MLGraphBuilder(context);
 
 // Create MLOperandDescriptor object.
-const desc = {type: 'float32', dataType: 'float32', dimensions: TENSOR_DIMS};
+const desc = {dataType: 'float32', dimensions: TENSOR_DIMS};
 
 // constant1 is a constant MLOperand with the value 0.5.
 const constantBuffer1 = new Float32Array(TENSOR_SIZE).fill(0.5);
diff --git a/code/samples_repo.js b/code/samples_repo.js
index 5e3880bf..161dd863 100644
--- a/code/samples_repo.js
+++ b/code/samples_repo.js
@@ -3,7 +3,6 @@ const samples = [
   'mul_add.js',
   'simple_graph.js',
   'matmul.js',
-  'optional_outputs.js',
 ];
 
 class SamplesRepository {