diff --git a/tfjs-converter/src/executor/graph_executor.ts b/tfjs-converter/src/executor/graph_executor.ts
index 845b653ee99..cf998a38af5 100644
--- a/tfjs-converter/src/executor/graph_executor.ts
+++ b/tfjs-converter/src/executor/graph_executor.ts
@@ -645,9 +645,8 @@ export class GraphExecutor implements FunctionExecutor {
   private mapInputs(inputs: NamedTensorMap) {
     const result: NamedTensorMap = {};
     for (const inputName in inputs) {
-      if (this._signature != null && this._signature.inputs != null &&
-          this._signature.inputs[inputName] != null) {
-        const tensor = this._signature.inputs[inputName];
+      const tensor = this._signature?.inputs?.[inputName];
+      if (tensor != null) {
         result[tensor.name] = inputs[inputName];
       } else {
         result[inputName] = inputs[inputName];
@@ -670,9 +669,8 @@ export class GraphExecutor implements FunctionExecutor {
 
   private mapOutputs(outputs: string[]) {
     return outputs.map(name => {
-      if (this._signature != null && this._signature.outputs != null &&
-          this._signature.outputs[name] != null) {
-        const tensor = this._signature.outputs[name];
+      const tensor = this._signature?.outputs?.[name];
+      if (tensor != null) {
         return tensor.name;
       }
       return name;
diff --git a/tfjs-converter/src/executor/graph_model.ts b/tfjs-converter/src/executor/graph_model.ts
index 666caf07685..ef9c8ad57a1 100644
--- a/tfjs-converter/src/executor/graph_model.ts
+++ b/tfjs-converter/src/executor/graph_model.ts
@@ -387,9 +387,10 @@ export class GraphModel<ModelURL extends Url = string | io.IOHandler> implements
                           NamedTensorMap): NamedTensorMap {
     if (!(inputs instanceof Tensor) && !Array.isArray(inputs)) {
       // The input is already a NamedTensorMap.
-      if (this.signature != null && this.signature.inputs != null) {
-        for (const input in this.signature.inputs) {
-          const tensor = this.signature.inputs[input];
+      const signatureInputs = this.signature?.inputs;
+      if (signatureInputs != null) {
+        for (const input in signatureInputs) {
+          const tensor = signatureInputs[input];
           if (tensor.resourceId != null) {
             inputs[input] = this.resourceIdToCapturedInput[tensor.resourceId];
           }
@@ -410,10 +411,9 @@ export class GraphModel<ModelURL extends Url = string | io.IOHandler> implements
 
     let inputIndex = 0;
     return this.inputNodes.reduce((map, inputName) => {
-      const signature =
-          this.signature ? this.signature.inputs[inputName] : null;
-      if (signature != null && signature.resourceId != null) {
-        map[inputName] = this.resourceIdToCapturedInput[signature.resourceId];
+      const resourceId = this.signature?.inputs?.[inputName]?.resourceId;
+      if (resourceId != null) {
+        map[inputName] = this.resourceIdToCapturedInput[resourceId];
       } else {
         map[inputName] = (inputs as Tensor[])[inputIndex++];
       }
@@ -454,10 +454,11 @@ export class GraphModel<ModelURL extends Url = string | io.IOHandler> implements
     this.resourceIdToCapturedInput = {};
 
     if (this.initializerSignature) {
-      const outputNames = Object.keys(this.initializerSignature.outputs);
+      const signatureOutputs = this.initializerSignature.outputs;
+      const outputNames = Object.keys(signatureOutputs);
       for (let i = 0; i < outputNames.length; i++) {
         const outputName = outputNames[i];
-        const tensorInfo = this.initializerSignature.outputs[outputName];
+        const tensorInfo = signatureOutputs[outputName];
         this.resourceIdToCapturedInput[tensorInfo.resourceId] = outputs[i];
       }
     }
diff --git a/tfjs-converter/src/executor/graph_model_test.ts b/tfjs-converter/src/executor/graph_model_test.ts
index 9800f4b62ac..7d3a3ade14f 100644
--- a/tfjs-converter/src/executor/graph_model_test.ts
+++ b/tfjs-converter/src/executor/graph_model_test.ts
@@ -125,6 +125,20 @@ const SIMPLE_HTTP_MODEL_LOADER = {
   }
 };
 
+const NO_INPUT_SIGNATURE_MODEL_LOADER = {
+  load: async () => {
+    return {
+      modelTopology: SIMPLE_MODEL,
+      weightSpecs: weightsManifest,
+      weightData: bias.dataSync(),
+      format: 'tfjs-graph-model',
+      generatedBy: '1.15',
+      convertedBy: '1.3.1',
+      userDefinedMetadata: {signature: {outputs: SIGNATURE.outputs}}
+    };
+  }
+};
+
 const CUSTOM_OP_MODEL: tensorflow.IGraphDef = {
   node: [
     {
@@ -479,10 +493,11 @@ describe('loadGraphModelSync', () => {
       weightsManifest: [{paths: [], weights: weightsManifest}],
     };
     expect(() => {
-      return loadGraphModelSync([modelJson] as unknown as [io.ModelJSON,
-                                                           ArrayBuffer]);
-    }).toThrowMatching(err =>
-      err.message.includes('weights must be the second element'));
+      return loadGraphModelSync(
+          [modelJson] as unknown as [io.ModelJSON, ArrayBuffer]);
+    })
+        .toThrowMatching(
+            err => err.message.includes('weights must be the second element'));
   });
 
   it('Throws an error if modelJSON is missing \'modelTopology\'', () => {
@@ -492,8 +507,9 @@ describe('loadGraphModelSync', () => {
     const weights = new Int32Array([5]).buffer;
     expect(() => {
       return loadGraphModelSync([badInput as io.ModelJSON, weights]);
-    }).toThrowMatching(err =>
-      err.message.includes('missing \'modelTopology\''));
+    })
+        .toThrowMatching(
+            err => err.message.includes('missing \'modelTopology\''));
   });
 
   it('Throws an error if modelJSON is missing \'weightsManifest\'', () => {
@@ -503,16 +519,16 @@ describe('loadGraphModelSync', () => {
     const weights = new Int32Array([5]).buffer;
     expect(() => {
       return loadGraphModelSync([badInput as io.ModelJSON, weights]);
-    }).toThrowMatching(err =>
-      err.message.includes('missing \'weightsManifest\''));
+    })
+        .toThrowMatching(
+            err => err.message.includes('missing \'weightsManifest\''));
   });
 
   it('Throws an error if modelSource is an unknown format', () => {
     const badInput = {foo: 'bar'};
     expect(() => {
       return loadGraphModelSync(badInput as io.ModelArtifacts);
-    }).toThrowMatching(err =>
-      err.message.includes('Unknown model format'));
+    }).toThrowMatching(err => err.message.includes('Unknown model format'));
   });
 
   it('Expect an error when moderUrl is null', () => {
@@ -774,6 +790,36 @@ describe('Model', () => {
     });
   });
 
+  describe('no signature input model', () => {
+    beforeEach(() => {
+      spyIo.getLoadHandlers.and.returnValue([NO_INPUT_SIGNATURE_MODEL_LOADER]);
+      spyIo.browserHTTPRequest.and.returnValue(NO_INPUT_SIGNATURE_MODEL_LOADER);
+    });
+
+    it('load', async () => {
+      const loaded = await model.load();
+      expect(loaded).toBe(true);
+    });
+
+    describe('predict', () => {
+      it('should generate default output', async () => {
+        await model.load();
+        const input = tfc.tensor2d([1, 1], [2, 1], 'int32');
+        const output = model.execute({'Input': input});
+        expect((output as tfc.Tensor).dataSync()[0]).toEqual(3);
+      });
+    });
+
+    describe('execute', () => {
+      it('should generate default output', async () => {
+        await model.load();
+        const input = tfc.tensor2d([1, 1], [2, 1], 'int32');
+        const output = model.execute(input);
+        expect((output as tfc.Tensor).dataSync()[0]).toEqual(3);
+      });
+    });
+  });
+
   describe('structured outputs model', () => {
     beforeEach(() => {
       spyIo.getLoadHandlers.and.returnValue([STRUCTURED_OUTPUTS_MODEL_LOADER]);