Error: Based on the provided shape, [256,108], and dtype float32, the tensor should have 27648 values but has 434

TensorFlow.js version

0.13.0

Browser version

Version 69.0.3497.100 - 64 bit

Describe the problem or feature request

I have trained the translation LSTM example here with default values and the parallel corpus provided by Anki (fr-en). I get this error

Error: Based on the provided shape, [256,108], and dtype float32, the tensor should have 27648 values but has 434
    at assert (tf-core.esm.js:17)
    at new e (tf-core.esm.js:17)
    at Function.e.make (tf-core.esm.js:17)
    at tensor (tf-core.esm.js:17)
    at o (tf-core.esm.js:17)
    at Object.decodeWeights (tf-core.esm.js:17)
    at tf-layers.esm.js:17
    at tf-layers.esm.js:17
    at Object.next (tf-layers.esm.js:17)
    at o (tf-layers.esm.js:17)
loadHostedPretrainedModel @ loader.js:50
async function (async)
loadHostedPretrainedModel @ loader.js:42
init @ index.js:41
button.addEventListener @ index.js:206
14:57:42.394 ui.js:19 Loading pretrained model failed.

when loading the model in the tensorflow-js example here

Code to reproduce the bug / link to feature request

I have put model.json here the metadata.json here and you can download the model shard from here

group1-shard1of1.zip

[AxelWolf]

We can reproduce this error msg in a browser (Chrome) environment:

“Uncaught (in promise) Error: Based on the provided shape, [1280], the tensor should have 1280 values but has 1279”

In our setup, the error occurs up after making small changes to a model (adding a class to the final classification layer), retraining and exporting. When loading the page that imports the model, it seems that the browser delivers the cached shards from the older model but the updated model.json. Solution is to clear the browser cache and reload the page.

[nebrelbug]

I ran into this issue when using the serve NPM/Yarn package. It seems to not work well with TensorflowJS. When I used Firebase Serve, it worked great.