resetting step count resets the samples processed and other metrics

README.md

@@ -147,16 +147,17 @@ And some experimental sampling flags you can use too (your mileage will ***defin
 ## To-Do
 
 * train and release a ***good*** model.
+  - the current model seems to require a ***long*** time of training at a very small LR rate to try and cover a wide variety of speakers of varying acoustics.
 * clean up the README, and document, document, document onto the wiki.
 * extend to ~~multiple languages ([VALL-E X](https://arxiv.org/abs/2303.03926)) and~~ addditional tasks ([SpeechX](https://arxiv.org/abs/2308.06873)).
+  - training additional tasks needs the SpeechX implementation to be reworked.
 * improve throughput (despite peaking at 120it/s):
-  - properly utilize RetNet's recurrent forward / chunkwise forward passes
+  - properly utilize RetNet's recurrent forward / chunkwise forward passes (does not seem to want to work no matter how the model is trained).
   - utilize an approach similar to [FasterDecoding/Medusa](https://github.com/FasterDecoding/Medusa/) with additional heads for decoding N+1, N+2, N+3 AR tokens
     + this requires a properly trained AR, however.
 * work around issues with extending context past what's trained (despite RetNet's retention allegedly being able to defeat this):
   - "sliding" AR input, such as have the context a fixed length.
-    + may require additional training to be aware of this, might not.
-    + may require some phoneme/codec alignment, might not.
+    + the model may need to be trained for this with a fancy positional embedding injected. Naively sliding the context window while making use of the RetNet implementation's positional embedding doesn't seem fruitful.
 
 ## Notices and Citations
 

vall_e/engines/base.py

@@ -321,6 +321,9 @@ class Engines(dict[str, Engine]):
 			)
 			if cfg.trainer.restart_step_count:
 				engine.global_steps = 0
+				engine.mocro_step = 0
+				engine.global_samples = 0
+				engine.tokens_processed = 0
 
 		# update the LR because for some god awful reason it gets overwritten when loading from a checkpoint but only when it's not using a scheduler
 		if cfg.hyperparameters.scheduler_type == "":