Error importing a keras model: Unknown layer: Dot

[huguesg12]

0.9.0, (and also 0.8.0)

Firefox & Chrome

I tried implementing the 'How to import a Keras Model into TensorFlow.js' tutorial, but could not manage to import my model, and got an: 'Uncaught (in promise) Error: Constructing tensor of shape (28) should match the length of values (22)' which I cannot make sense of. In particular, 28 is the actual number of output units of my model, but I really do not understand where that 22 comes from.
The test page is at: http://huguesg.fr/incidents/test.html
The model.json file is: http://huguesg.fr/incidents/model.json and the 3 shards are also in the same folder.
I tried creating the files both with the tfjs.converters.save_keras_model function or the tensorflowjs_converter function after saving the model as .h5, but neither worked.

[bileschi]

I am able to reproduce this issue. Looking into it.

[huguesg12]

Thanks. If necessary, I also dropped the .h5 file at http://huguesg.fr/incidents/onehot29model.h5

[bileschi]

The issue seems to be related to missing bytes in the weights files.
The manifiest claims that the first groupBuffer contains two weights, "dense_1/kernel" with size [64, 28], and "dense_1/bias" with size [28]. It expects the first 7168 = 4 * 64 * 28 bytes to be the kernel, and the next 112 = 4 * 28 bytes to be the bias. Thus, it's looking for 7280 = 7168 + 112 bytes in the first weights file. However, the file 'group1-shard1of1' only contains 7256 bytes. This is representing as a shape error when building the tensor.

Now, the mystery is why the weights file is fewer bytes than we expect! My next step is to look at the .h5 file to see if it's contains any clues.

[bileschi]

h5py seems to indicate that the weights are the correct sizes.

I then tried converting locally, and it seems to have created a group1 file with the correct size. Can you try making sure your converter is up to date (pip install) and running again on your .h5 file?

$ tensorflowjs_converter --input_format keras ./onehot29model.h5 .

...

$ \ls -al
total 832
drwxr-xr-x   7 bileschi  eng     224 Apr 23 16:57 .
drwxr-xr-x+ 48 bileschi  eng    1536 Apr 23 16:55 ..
-rw-r--r--   1 bileschi  eng    7280 Apr 23 16:57 group1-shard1of1
-rw-r--r--   1 bileschi  eng    6464 Apr 23 16:57 group2-shard1of1
-rw-r--r--   1 bileschi  eng   82944 Apr 23 16:57 group3-shard1of1
-rw-r--r--   1 bileschi  eng    3232 Apr 23 16:57 model.json
-rw-r--r--@  1 bileschi  eng  318256 Apr 23 16:56 onehot29model.h5

[huguesg12]

I updated tensorflowjs (which I installed yesterday, but then updated keras before outputing these files). I know have the right size for the files, but a new error is now occuring : Uncaught (in promise) RangeError: byte length of Float32Array should be a multiple of 4 The new files are at the same adress : http://huguesg.fr/incidents/ 2018-04-23 23:01 GMT+02:00 Stanley Bileschi <notifications@github.com>:

…

h5py seems to indicate that the weights are the correct sizes. I then tried converting locally, and it seems to have created a group1 file with the correct size. Can you try making sure your converter is up to date (pip install) and running again on your .h5 file? $ tensorflowjs_converter --input_format keras ./onehot29model.h5 . ... $ \ls -al total 832 drwxr-xr-x 7 bileschi eng 224 Apr 23 16:57 . drwxr-xr-x+ 48 bileschi eng 1536 Apr 23 16:55 .. -rw-r--r-- 1 bileschi eng 7280 Apr 23 16:57 group1-shard1of1 -rw-r--r-- 1 bileschi eng 6464 Apr 23 16:57 group2-shard1of1 -rw-r--r-- 1 bileschi eng 82944 Apr 23 16:57 group3-shard1of1 -rw-r--r-- 1 bileschi eng 3232 Apr 23 16:57 model.json -rw-r--r--@ 1 bileschi eng 318256 Apr 23 16:56 onehot29model.h5 — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#218 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/APNdtyfx_hh2KYGye9nvB0crnJkWWi6Eks5trkFHgaJpZM4Tfvdj> .

[Rafi993]

I do have similar issue. After importing when I run the code it says

tfjs@0.9.0:1 Uncaught (in promise) Error: Unknown layer: Dot
    at new t (tfjs@0.9.0:1)
    at Object.n.deserializeKerasObject (tfjs@0.9.0:1)
    at Object.n.deserialize (tfjs@0.9.0:1)
    at p (tfjs@0.9.0:1)
    at t.fromConfig (tfjs@0.9.0:1)
    at Object.n.deserializeKerasObject (tfjs@0.9.0:1)
    at Object.n.deserialize (tfjs@0.9.0:1)
    at tfjs@0.9.0:1
    at r (tfjs@0.9.0:1)
    at Object.next (tfjs@0.9.0:1)

[Rafi993]

I did try updating tfjs to version 0.10.2. I do seem to get the following error now. It would be really helpful if anyone can solve this. It is driving me nuts

tf.js:531 Uncaught (in promise) Error: No backend found in registry.
    at Environment.getBestBackendType (tf.js:531)
    at Environment.evaluateFeature (tf.js:547)
    at Environment.get (tf.js:522)
    at Environment.initDefaultBackend (tf.js:634)
    at Environment.get [as engine] (tf.js:626)
    at Object.Tracking.tidy (tf.js:7701)
    at Object.descriptor.value [as randomUniform] (tf.js:4359)
    at Object.randomUniform (tf.js:9847)
    at RandomUniform.apply (tf.js:15275)
    at Embedding.Layer.addWeight (tf.js:11977)
Environment.getBestBackendType @ tf.js:531
Environment.evaluateFeature @ tf.js:547
Environment.get @ tf.js:522
Environment.initDefaultBackend @ tf.js:634
get @ tf.js:626
Tracking.tidy @ tf.js:7701
descriptor.value @ tf.js:4359
randomUniform @ tf.js:9847
RandomUniform.apply @ tf.js:15275
Layer.addWeight @ tf.js:11977
Embedding.build @ tf.js:16635
(anonymous) @ tf.js:11891
nameScope @ tf.js:11151
nameScope @ tf.js:10364
Layer.apply @ tf.js:11883
Sequential.add @ tf.js:19825
Sequential.fromConfig @ tf.js:19992
deserializeKerasObject @ tf.js:20582
deserialize @ tf.js:19125
processLayer @ tf.js:12885
Container.fromConfig @ tf.js:12902
deserializeKerasObject @ tf.js:20582
deserialize @ tf.js:19125
(anonymous) @ tf.js:19745
step @ tf.js:19720
(anonymous) @ tf.js:19701
(anonymous) @ tf.js:19695
__awaiter @ tf.js:19691
modelFromJSON @ tf.js:19735
(anonymous) @ tf.js:19786
step @ tf.js:19720
(anonymous) @ tf.js:19701
fulfilled @ tf.js:19692
Promise.then (async)
(anonymous) @ index.js:68

[Rafi993]

This is the model I have been trying to convert https://github.com/priya-dwivedi/Deep-Learning/blob/master/qa_chat_bot/model6.h5

[dsmilkov]

Hi @Rafi993 , regarding the "No backend found in registry." error - there was a problem with 0.10.2. We just released 0.10.3 and that problem should (hopefully) go away.

[Rafi993]

thanks @dsmilkov but after updating to 0.10.3 I have the error

Uncaught (in promise) Error: Unknown layer: Dot
    at new t (tfjs@0.10.3:1)
    at Object.n.deserializeKerasObject (tfjs@0.10.3:1)
    at Object.n.deserialize (tfjs@0.10.3:1)
    at p (tfjs@0.10.3:1)
    at t.fromConfig (tfjs@0.10.3:1)
    at Object.n.deserializeKerasObject (tfjs@0.10.3:1)
    at Object.n.deserialize (tfjs@0.10.3:1)
    at tfjs@0.10.3:1
    at r (tfjs@0.10.3:1)
    at Object.next (tfjs@0.10.3:1)

This was the trained model https://gist.github.com/Rafi993/aff598b4c06a4a70a4893f4ee62c25f4#file-trained-model-L140 . the error was in Line 140 "class_name" with value "Dot"

[huguesg12]

Still have the same error here with 0.10.3 : tfjs@0.10.3:1 Uncaught (in promise) RangeError: byte length of Float32Array should be a multiple of 4 at typedArrayConstructByArrayBuffer (<anonymous>) at new Float32Array (native) at https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.10.3:1:312391 at Array.forEach (<anonymous>) at https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.10.3:1:312275 at Array.forEach (<anonymous>) at Object.<anonymous> ( https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.10.3:1:312063) at r (https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.10.3:1:310574) at Object.next ( https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.10.3:1:309909) at o (https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.10.3:1:309651) 2018-04-24 5:43 GMT+02:00 Rafi <notifications@github.com>:

…

thanks @dsmilkov <https://github.com/dsmilkov> but now I have the error Uncaught (in promise) Error: Unknown layer: Dot at new t ***@***.***:1) at Object.n.deserializeKerasObject ***@***.***:1) at Object.n.deserialize ***@***.***:1) at p ***@***.***:1) at t.fromConfig ***@***.***:1) at Object.n.deserializeKerasObject ***@***.***:1) at Object.n.deserialize ***@***.***:1) at ***@***.***:1 at r ***@***.***:1) at Object.next ***@***.***:1) — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#218 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/APNdt1XwYE8wnOXVSOWPhVQM9sKcVqZYks5trp96gaJpZM4Tfvdj> .

[bileschi]

I was able to load the model using 0.10.3.

Can you report the size of the weight shards created by converter? Can you also make sure that your browser is not caching older, incorrect values of the weights?

The sizes converter created here are:

-rw-r--r--   1 bileschi primarygroup    7280 Apr 24 10:13 group1-shard1of1
-rw-r--r--   1 bileschi primarygroup    6464 Apr 24 10:13 group2-shard1of1
-rw-r--r--   1 bileschi primarygroup   82944 Apr 24 10:13 group3-shard1of1

You can force reloading of the cached elements in chrome with ctl + shift + r .

[huguesg12]

I do have exactly the same size, and tried reloading as advised, but still get the same error. Have you tried with the files on http://huguesg.fr/incidents/ ? 2018-04-24 16:31 GMT+02:00 Stanley Bileschi <notifications@github.com>:

…

I was able to load the model using 0.10.3. Can you report the size of the weight shards created by converter? Can you also make sure that your browser is not caching older, incorrect values of the weights? The sizes converter created here are: -rw-r--r-- 1 bileschi primarygroup 7280 Apr 24 10:13 group1-shard1of1 -rw-r--r-- 1 bileschi primarygroup 6464 Apr 24 10:13 group2-shard1of1 -rw-r--r-- 1 bileschi primarygroup 82944 Apr 24 10:13 group3-shard1of1 You can force reloading of the cached elements in chrome with ctl + shift + r . — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#218 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/APNdt1kRw430zPwtpKkIDI4sHgw8WPoLks5trzcwgaJpZM4Tfvdj> .

[caisq]

Began working on this. Will send a PR soon.

[freekoy]

Same problem?How to solve it？
`
io_utils.ts:116 Uncaught (in promise) RangeError: byte length of Float32Array should be a multiple of 4
at new Float32Array ()
at o (io_utils.ts:116)
at Object.decodeWeights (io_utils.ts:79)
at e. (frozen_model.ts:109)
at exports_regularizers.ts:47
at Object.next (exports_regularizers.ts:47)
at s (exports_regularizers.ts:47)

o @ io_utils.ts:116
decodeWeights @ io_utils.ts:79
(anonymous) @ frozen_model.ts:109
(anonymous) @ exports_regularizers.ts:47
(anonymous) @ exports_regularizers.ts:47
s @ exports_regularizers.ts:47
Promise.then (async)
c @ coco-ssd.esm.js:2
(anonymous) @ coco-ssd.esm.js:2
__awaiter @ coco-ssd.esm.js:2
load @ coco-ssd.esm.js:2
window.onload @ index.js:26
load (async)
parcelRequire.index.js.@tensorflow-models/coco-ssd @ index.js:26
newRequire @ demo.e31bb0bc.js:49
(anonymous) @ demo.e31bb0bc.js:81
(anonymous) @ demo.e31bb0bc.js:107
`

[YajJackson]

Also running into this issue when running tf.loadModel('./tfjs-models/MOBILENET/model.json');
MOBILENET/ was generated from tfjs.converters.save_keras_model(mobilenet, './tfjs-models/MOBILENET')

Uncaught (in promise) RangeError: byte length of Float32Array should be a multiple of 4
    at new Float32Array (<anonymous>)
    at o (io_utils.ts:116)
    at Object.decodeWeights (io_utils.ts:79)
    at models.ts:287
    at index.ts:68
    at Object.next (index.ts:68)
    at o (index.ts:68)

Any help would be much appreciated.

[caisq]

I don't think the issue that @YajJackson and @freekoy is running into is related to the Dot layer. The issue is being tracked in #924

Closing this PR again.