Improve error message in tensorXd

src/ops/array_ops.ts

@@ -31,6 +31,7 @@ import {ConcatOps} from './concat';
 import {operation} from './operation';
 import {MPRandGauss} from './rand';
 import {SegmentOps} from './segment_ops';
+import {assertNonNull} from '../util';
 
 export class ArrayOps {
   /**
@@ -119,6 +120,7 @@ export class ArrayOps {
   @doc({heading: 'Tensors', subheading: 'Creation'})
   static tensor1d(values: TensorLike1D, dtype: DataType = 'float32'): Tensor1D {
     const inferredShape = util.inferShape(values);
+    assertNonNull(values);
     if (inferredShape.length !== 1) {
       throw new Error('tensor1d() requires values to be a flat/TypedArray');
     }
@@ -150,6 +152,7 @@ export class ArrayOps {
   static tensor2d(
       values: TensorLike2D, shape?: [number, number],
       dtype: DataType = 'float32'): Tensor2D {
+    assertNonNull(values);
     if (shape != null && shape.length !== 2) {
       throw new Error('tensor2d() requires shape to have two numbers');
     }
@@ -192,6 +195,7 @@ export class ArrayOps {
   static tensor3d(
       values: TensorLike3D, shape?: [number, number, number],
       dtype: DataType = 'float32'): Tensor3D {
+    assertNonNull(values);
     if (shape != null && shape.length !== 3) {
       throw new Error('tensor3d() requires shape to have three numbers');
     }
@@ -234,6 +238,7 @@ export class ArrayOps {
   static tensor4d(
       values: TensorLike4D, shape?: [number, number, number, number],
       dtype: DataType = 'float32'): Tensor4D {
+    assertNonNull(values);
     if (shape != null && shape.length !== 4) {
       throw new Error('tensor4d() requires shape to have four numbers');
     }
@@ -276,6 +281,7 @@ export class ArrayOps {
   static tensor5d(
       values: TensorLike5D, shape?: [number, number, number, number, number],
       dtype: DataType = 'float32'): Tensor5D {
+    assertNonNull(values);
     if (shape != null && shape.length !== 5) {
       throw new Error('tensor5d() requires shape to have five numbers');
     }
@@ -319,6 +325,7 @@ export class ArrayOps {
       values: TensorLike6D,
       shape?: [number, number, number, number, number, number],
       dtype: DataType = 'float32'): Tensor6D {
+    assertNonNull(values);
     if (shape != null && shape.length !== 6) {
       throw new Error('tensor6d() requires shape to have six numbers');
     }

src/tensor_test.ts

@@ -271,6 +271,12 @@ describeWithFlags('tensor', ALL_ENVS, () => {
     expectArraysClose(a, [1, 2, 3]);
   });
 
+  it('tf.tensor1d() throw error with null input value', () => {
+    expect(() => tf.tensor1d(null))
+        .toThrowError('The input to the tensor constructor ' +
+            'must be a non-null value.');
+  });
+
   it('tf.tensor1d() from number[][], shape mismatch', () => {
     // tslint:disable-next-line:no-any
     expect(() => tf.tensor1d([[1], [2], [3]] as any)).toThrowError();
@@ -296,6 +302,12 @@ describeWithFlags('tensor', ALL_ENVS, () => {
     expect(() => tf.tensor2d([1, 2, 3, 4])).toThrowError();
   });
 
+  it('tf.tensor2d() throw error with null input value', () => {
+    expect(() => tf.tensor2d(null))
+        .toThrowError('The input to the tensor constructor ' +
+            'must be a non-null value.');
+  });
+
   it('tensor3d() from number[][][]', () => {
     const a = tf.tensor3d([[[1], [2], [3]], [[4], [5], [6]]], [2, 3, 1]);
     expectArraysClose(a, [1, 2, 3, 4, 5, 6]);
@@ -317,6 +329,12 @@ describeWithFlags('tensor', ALL_ENVS, () => {
     expect(() => tf.tensor3d([1, 2, 3, 4], shape)).toThrowError();
   });
 
+  it('tf.tensor3d() throw error with null input value', () => {
+    expect(() => tf.tensor3d(null))
+        .toThrowError('The input to the tensor constructor ' +
+            'must be a non-null value.');
+  });
+
   it('tensor4d() from number[][][][]', () => {
     const a = tf.tensor4d([[[[1]], [[2]]], [[[4]], [[5]]]], [2, 2, 1, 1]);
     expectArraysClose(a, [1, 2, 4, 5]);
@@ -340,6 +358,24 @@ describeWithFlags('tensor', ALL_ENVS, () => {
     expect(() => tf.tensor4d([1, 2, 3, 4], shape)).toThrowError();
   });
 
+  it('tf.tensor4d() throw error with null input value', () => {
+    expect(() => tf.tensor4d(null))
+        .toThrowError('The input to the tensor constructor ' +
+            'must be a non-null value.');
+  });
+
+  it('tf.tensor5d() throw error with null input value', () => {
+    expect(() => tf.tensor5d(null))
+        .toThrowError('The input to the tensor constructor ' +
+            'must be a non-null value.');
+  });
+
+  it('tf.tensor6d() throw error with null input value', () => {
+    expect(() => tf.tensor6d(null))
+        .toThrowError('The input to the tensor constructor ' +
+            'must be a non-null value.');
+  });
+
   it('default dtype', () => {
     const a = tf.scalar(3);
     expect(a.dtype).toBe('float32');

src/util.ts

@@ -16,7 +16,7 @@
  */
 import {Tensor} from './tensor';
 // tslint:disable-next-line:max-line-length
-import {DataType, DataTypeMap, FlatVector, NamedTensorMap, RecursiveArray, RegularArray, TensorContainer, TensorContainerArray, TypedArray} from './types';
+import {DataType, DataTypeMap, FlatVector, NamedTensorMap, RecursiveArray, RegularArray, TensorContainer, TensorContainerArray, TensorLike, TypedArray} from './types';
 
 function assertArgumentIsTensor(
     x: Tensor, argName: string, functionName: string) {
@@ -100,6 +100,12 @@ export function assertTypesMatch(a: Tensor, b: Tensor): void {
           ` second(${b.dtype}) input must match`);
 }
 
+export function assertNonNull(a: TensorLike): void {
+  assert(
+      a != null,
+      `The input to the tensor constructor must be a non-null value.`);
+}
+
 // NOTE: We explicitly type out what T extends instead of any so that
 // util.flatten on a nested array of number doesn't try to infer T as a
 // number[][], causing us to explicitly type util.flatten<number>().