Update code editor sample to the latst implementation (#193)

* Use MLGraphBuilder.constant(desc, value) for scalar
* Use `gemm` which supports 2Dx2D
* Use MLOperandDescriptor.dataType
* Remove optional output sample

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);

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);

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);

code/samples_repo.js

@@ -3,7 +3,6 @@ const samples = [
   'mul_add.js',
   'simple_graph.js',
   'matmul.js',
-  'optional_outputs.js',
 ];
 
 class SamplesRepository {