[node]Add node binding api to get number of loaded SavedModel

tfjs-node/binding/tfjs_backend.cc

@@ -1218,4 +1218,13 @@ napi_value TFJSBackend::RunSavedModel(napi_env env,
   return output_tensor_infos;
 }
 
+napi_value TFJSBackend::GetNumOfSavedModels(napi_env env) {
+  napi_status nstatus;
+  napi_value num_saved_models;
+  nstatus =
+      napi_create_int32(env, tf_savedmodel_map_.size(), &num_saved_models);
+  ENSURE_NAPI_OK_RETVAL(env, nstatus, nullptr);
+  return num_saved_models;
+}
+
 }  // namespace tfnodejs

tfjs-node/binding/tfjs_backend.h

@@ -80,6 +80,9 @@ class TFJSBackend {
                            napi_value input_op_names,
                            napi_value output_op_names);
 
+  // Get number of loaded SavedModel in the backend:
+  napi_value GetNumOfSavedModels(napi_env env);
+
  private:
   TFJSBackend(napi_env env);
   ~TFJSBackend();

tfjs-node/binding/tfjs_binding.cc

@@ -224,6 +224,11 @@ static napi_value RunSavedModel(napi_env env, napi_callback_info info) {
   return gBackend->RunSavedModel(env, args[0], args[1], args[2], args[3]);
 }
 
+static napi_value GetNumOfSavedModels(napi_env env, napi_callback_info info) {
+  // Delete SavedModel takes 0 param;
+  return gBackend->GetNumOfSavedModels(env);
+}
+
 static napi_value InitTFNodeJSBinding(napi_env env, napi_value exports) {
   napi_status nstatus;
 
@@ -255,6 +260,8 @@ static napi_value InitTFNodeJSBinding(napi_env env, napi_value exports) {
        napi_default, nullptr},
       {"isUsingGpuDevice", nullptr, IsUsingGPUDevice, nullptr, nullptr, nullptr,
        napi_default, nullptr},
+      {"getNumOfSavedModels", nullptr, GetNumOfSavedModels, nullptr, nullptr,
+       nullptr, napi_default, nullptr},
   };
   nstatus = napi_define_properties(env, exports, ARRAY_SIZE(exports_properties),
                                    exports_properties);

tfjs-node/src/node.ts

@@ -21,7 +21,7 @@
 
 import {tensorBoard} from './callbacks';
 import {decodeBmp, decodeGif, decodeImage, decodeJpeg, decodePng, encodeJpeg, encodePng} from './image';
-import {getMetaGraphsFromSavedModel, loadSavedModel} from './saved_model';
+import {getMetaGraphsFromSavedModel, getNumOfSavedModels, loadSavedModel} from './saved_model';
 import {summaryFileWriter} from './tensorboard';
 
 export const node = {
@@ -35,5 +35,6 @@ export const node = {
   summaryFileWriter,
   tensorBoard,
   getMetaGraphsFromSavedModel,
+  getNumOfSavedModels,
   loadSavedModel
 };

tfjs-node/src/nodejs_kernel_backend.ts

@@ -25,6 +25,7 @@ import {isArray, isNullOrUndefined} from 'util';
 
 import {Int64Scalar} from './int64_tensors';
 import {TensorMetadata, TFEOpAttr, TFJSBinding} from './tfjs_binding';
+
 type TensorData = {
   shape: number[],
   dtype: number,
@@ -1962,6 +1963,10 @@ export class NodeJSKernelBackend extends KernelBackend {
     const elapsed = process.hrtime(start);
     return {kernelMs: elapsed[0] * 1000 + elapsed[1] / 1000000};
   }
+
+  getNumOfSavedModels() {
+    return this.binding.getNumOfSavedModels();
+  }
 }
 
 /** Returns an instance of the Node.js backend. */

tfjs-node/src/saved_model.ts

@@ -437,3 +437,9 @@ function mapTFDtypeToJSDtype(tfDtype: string): DataType {
       throw new Error('Unsupported tensor DataType: ' + tfDtype);
   }
 }
+
+export function getNumOfSavedModels() {
+  ensureTensorflowBackend();
+  const backend = nodeBackend();
+  return backend.getNumOfSavedModels();
+}

tfjs-node/src/saved_model_test.ts

@@ -233,6 +233,7 @@ describe('SavedModel', () => {
   });
 
   it('load TFSavedModel and delete', async () => {
+    expect(tf.node.getNumOfSavedModels()).toBe(0);
     const loadSavedModelMetaGraphSpy =
         spyOn(nodeBackend(), 'loadSavedModelMetaGraph').and.callThrough();
     const deleteSavedModelSpy =
@@ -244,9 +245,11 @@ describe('SavedModel', () => {
         'serving_default');
     expect(loadSavedModelMetaGraphSpy).toHaveBeenCalledTimes(1);
     expect(deleteSavedModelSpy).toHaveBeenCalledTimes(0);
+    expect(tf.node.getNumOfSavedModels()).toBe(1);
     model.dispose();
     expect(loadSavedModelMetaGraphSpy).toHaveBeenCalledTimes(1);
     expect(deleteSavedModelSpy).toHaveBeenCalledTimes(1);
+    expect(tf.node.getNumOfSavedModels()).toBe(0);
   });
 
   it('delete TFSavedModel multiple times throw exception', async done => {
@@ -265,6 +268,7 @@ describe('SavedModel', () => {
 
   it('load multiple signatures from the same metagraph only call binding once',
      async () => {
+       expect(tf.node.getNumOfSavedModels()).toBe(0);
        const backend = nodeBackend();
        const loadSavedModelMetaGraphSpy =
            spyOn(backend, 'loadSavedModelMetaGraph').and.callThrough();
@@ -273,13 +277,17 @@ describe('SavedModel', () => {
            './test_objects/saved_model/module_with_multiple_signatures',
            ['serve'], 'serving_default');
        expect(loadSavedModelMetaGraphSpy).toHaveBeenCalledTimes(1);
+       expect(tf.node.getNumOfSavedModels()).toBe(1);
        const model2 = await tf.node.loadSavedModel(
            './test_objects/saved_model/module_with_multiple_signatures',
            ['serve'], 'timestwo');
        expect(loadSavedModelMetaGraphSpy).toHaveBeenCalledTimes(1);
+       expect(tf.node.getNumOfSavedModels()).toBe(1);
        model1.dispose();
+       expect(tf.node.getNumOfSavedModels()).toBe(1);
        model2.dispose();
        expect(loadSavedModelMetaGraphSpy).toHaveBeenCalledTimes(1);
+       expect(tf.node.getNumOfSavedModels()).toBe(0);
      });
 
   it('load signature after delete call binding', async () => {
@@ -309,19 +317,20 @@ describe('SavedModel', () => {
   });
 
   it('throw error when input tensors do not match input ops', async done => {
+    const model = await tf.node.loadSavedModel(
+        './test_objects/saved_model/times_three_float', ['serve'],
+        'serving_default');
+    const input1 = tf.tensor1d([1.0, 2, 3]);
+    const input2 = tf.tensor1d([1.0, 2, 3]);
     try {
-      const model = await tf.node.loadSavedModel(
-          './test_objects/saved_model/times_three_float', ['serve'],
-          'serving_default');
-      const input1 = tf.tensor1d([1.0, 2, 3]);
-      const input2 = tf.tensor1d([1.0, 2, 3]);
       model.predict([input1, input2]);
       done.fail();
     } catch (error) {
       expect(error.message)
           .toBe(
               'Length of input op names (1) does not match the ' +
               'length of input tensors (2).');
+      model.dispose();
       done();
     }
   });
@@ -369,18 +378,19 @@ describe('SavedModel', () => {
   });
 
   it('execute model with wrong tensor name', async done => {
+    const model = await tf.node.loadSavedModel(
+        './test_objects/saved_model/times_three_float', ['serve'],
+        'serving_default');
+    const input = tf.tensor1d([1.0, 2, 3]);
     try {
-      const model = await tf.node.loadSavedModel(
-          './test_objects/saved_model/times_three_float', ['serve'],
-          'serving_default');
-      const input = tf.tensor1d([1.0, 2, 3]);
       model.predict({'xyz': input});
       done.fail();
     } catch (error) {
       expect(error.message)
           .toBe(
               'The model signatureDef input names are x, however ' +
               'the provided input names are xyz.');
+      model.dispose();
       done();
     }
   });
@@ -466,4 +476,20 @@ describe('SavedModel', () => {
     test_util.expectArraysClose(await output2.data(), [1, 2, 3]);
     model.dispose();
   });
+
+  it('load multiple models', async () => {
+    expect(tf.node.getNumOfSavedModels()).toBe(0);
+    const model1 = await tf.node.loadSavedModel(
+        './test_objects/saved_model/module_with_multiple_signatures', ['serve'],
+        'serving_default');
+    expect(tf.node.getNumOfSavedModels()).toBe(1);
+    const model2 = await tf.node.loadSavedModel(
+        './test_objects/saved_model/model_multi_output', ['serve'],
+        'serving_default');
+    expect(tf.node.getNumOfSavedModels()).toBe(2);
+    model1.dispose();
+    expect(tf.node.getNumOfSavedModels()).toBe(1);
+    model2.dispose();
+    expect(tf.node.getNumOfSavedModels()).toBe(0);
+  });
 });

tfjs-node/src/tfjs_binding.ts

@@ -60,6 +60,8 @@ export interface TFJSBinding {
       savedModelId: number, inputTensorIds: number[], inputOpNames: string,
       outputOpNames: string): TensorMetadata[];
 
+  getNumOfSavedModels(): number;
+
   isUsingGpuDevice(): boolean;
 
   // TF Types