[add] extended tests with modelset and modelrun

tests/test_client.ts

@@ -4,6 +4,9 @@ import {Tensor} from "../src/tensor";
 import {DType} from "../src/DType";
 import 'mocha';
 import {expect} from 'chai';
+import {Model} from "../src/Model";
+import * as fs from "fs";
+import {Backend} from "../src/Backend";
 
 const mochaAsync = (fn: any) => {
     return (done: any) => {
@@ -86,3 +89,41 @@ it("ai.tensorget negative testing", mochaAsync(async () => {
 }));
 
 
+it("ai.modelset positive testing", mochaAsync(async () => {
+    const nativeClient = createClient();
+    const aiclient = new RedisaiClient(nativeClient);
+    let model_blob: Buffer = fs.readFileSync("./tests/test_data/graph.pb");
+    const model = new Model(Backend.TF, "CPU", ["a", "b"], ["c"], model_blob);
+    const result = await aiclient.modelset("m1", model);
+    expect(result).to.equal('OK');
+    aiclient.end(true);
+}));
+
+it("ai.modelrun positive testing", mochaAsync(async () => {
+    const nativeClient = createClient();
+    const aiclient = new RedisaiClient(nativeClient);
+
+
+    const tensorA = new Tensor(DType.float32, [1, 2], [2, 3]);
+    const resultA = await aiclient.tensorset("tensorA", tensorA);
+    expect(resultA).to.equal('OK');
+
+    const tensorB = new Tensor(DType.float32, [1, 2], [3, 5]);
+    const resultB = await aiclient.tensorset("tensorB", tensorB);
+    expect(resultB).to.equal('OK');
+
+
+    let model_blob: Buffer = fs.readFileSync("./tests/test_data/graph.pb");
+    const model = new Model(Backend.TF, "CPU", ["a", "b"], ["c"], model_blob);
+    const resultModelSet = await aiclient.modelset("mymodel", model);
+    expect(resultModelSet).to.equal('OK');
+
+    const resultModelRun = await aiclient.modelrun("mymodel", ["tensorA","tensorB"], ["tensorC"]);
+    expect(resultModelRun).to.equal('OK');
+
+    const tensorC = await aiclient.tensorget("tensorC");
+    expect(tensorC.data[0]).to.closeTo(6.0,0.1);
+    expect(tensorC.data[1]).to.closeTo(15.0,0.1);
+
+    aiclient.end(true);
+}));