Problem when running TF.js with Jest (unit testing)

TensorFlow.js version

0.12.3

Browser version

Node.js 10.6.0 (no browser) Typescript 2.7.1

Describe the problem or feature request

I’m trying to use tf.sum() and tf.squaredDifference() (see below). Two issues – some or all might be my fault:

1. According to the docs, I can pass a tf.scalar to tf.squaredDifference; however, I get a Typescript error when passing a tf.scalar unless I cast to any. Seems it’s expecting a Tensor. Are the docs wrong, or is the Typescript definition too restrictive here?
2. When I run the below code to sum my tensor (vector), I get the error tensor1d() requires values to be a flat/TypedArray. This already should be a 1D tensor/vector, so why is tfjs complaining here? But moreover, the docs suggest I can sum with higher-order tensors as well, so not sure what the 1D restriction is about. Any ideas would be welcome!

Thanks in advance!

Code to reproduce the bug / link to feature request

    // state is a tf.Tensor1D
    console.log(state.squaredDifference(tf.scalar(0) as any).sum());

[ClementVidal]

After some investigation i think i found something interesting:

When using the NodeJSKernelBackend (tf.setBackend("tensorflow"))

In tfjs-core/src/tensor_util_env.ts:34 in function inferShape(), if i change to use Array.isArray() instead of instanceof, the @smith-kyle error goes away and everything work perfectly.

while ( Array.isArray( firstElem ) || isTypedArray(firstElem)) {

I suspect that there is a problem with jest patching some builtin objects like Array thus invalidating tests using instanceof.

I think Array.isArray() should be enforced instead of instanceof

PR 1503 aim to fix that.

[smith-kyle]

Can confirm that running with jest can cause this error to throw:

tensor1d() requires values to be a flat/TypedArray