Where to find 0.6.0a8 model

Where can I find models for the 0.6.0a8 binaries? (Specifically for the pi 4)

We have not yet released a v0.6 compatible model. So you would have to train and re-export yourself. This patch could help you re-use v0.5.1 checkpoints for that: https://gist.github.com/reuben/b68b9085f7b293580f8431156a33daa9

Do you have any guess on when 0.6 model might be available?

We do not yet, sorry.

@lissyx is there a way to continue training from 0.5.1 checkpoint using the 0.6.0a14 implementation? I am mainly interested in performing/adding the noise augmentation over a previously trained 0.5.1 checkpoint.

I shared that above already

Instead of applying patch in 0.5.1 i made following changes in 0.6a11

@@ -486,9 +487,19 @@ def train():

     # Checkpointing
+    def fixup(name):
+        if name.startswith('cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/'):
+            return name.replace('cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/', 'lstm_fused_cell/')
+        return name
+    mapping = {fixup(v.op.name): v for v in tfv1.global_variables()}
+    checkpoint_saver = tfv1.train.Saver(max_to_keep=FLAGS.max_to_keep,var_list = mapping)
     checkpoint_saver = tfv1.train.Saver(max_to_keep=FLAGS.max_to_keep)
     checkpoint_path = os.path.join(FLAGS.checkpoint_dir, 'train')

+    best_dev_saver = tfv1.train.Saver(max_to_keep=1,var_list = mapping)

It starts the training using ds051 checkpoint and later saved few checkpoints
so i thought once it has saved , i can remove patch and use new checkpoints to resume
the training

but if i remove the patch it do not load the newely generated checkpoint , and throws below error

Traceback (most recent call last):
  File "DeepSpeech.py", line 949, in <module>
  File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 299, in run
    _run_main(main, args)
  File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 250, in _run_main
  File "DeepSpeech.py", line 933, in main
  File "DeepSpeech.py", line 566, in train
    loaded = try_loading(session, checkpoint_saver, 'checkpoint', 'most recent')
  File "DeepSpeech.py", line 403, in try_loading
    saver.restore(session, checkpoint_path)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/training/saver.py", line 1302, in restore
    err, "a Variable name or other graph key that is missing")
tensorflow.python.framework.errors_impl.NotFoundError: Restoring from checkpoint failed. This is most likely due to a Variable name or other graph key that is missing from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

Key cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/bias not found in checkpoint
         [[node save/RestoreV2 (defined at DeepSpeech.py:498) ]]

anything i am missing here, ?

do we need this patch

Note that the patch just makes it load the weights, but the resulting model will perform really badly. You should not rely on models created using that flag.