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[add] extended tests with modelset and modelrun
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tests/test_client.ts

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

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