def get_mapped_symbol_weights(model_symbols: SymbolIdDict,
trained_weights: Tensor,
trained_symbols: SymbolIdDict,
custom_mapping: Optional[SymbolsMap],
hparams: HParams, logger: Logger) -> Tensor:
symbols_match_not_model = trained_weights.shape[0] != len(trained_symbols)
if symbols_match_not_model:
logger.exception(
f"Weights mapping: symbol space from pretrained model ({trained_weights.shape[0]}) did not match amount of symbols ({len(trained_symbols)})."
)
raise Exception()
if custom_mapping is None:
symbols_map = SymbolsMap.from_intersection(
map_to=model_symbols.get_all_symbols(),
map_from=trained_symbols.get_all_symbols(),
)
else:
symbols_map = custom_mapping
symbols_map.remove_unknown_symbols(
known_to_symbol=model_symbols.get_all_symbols(),
known_from_symbols=trained_symbols.get_all_symbols())
# Remove all empty mappings
symbols_wo_mapping = symbols_map.get_symbols_with_empty_mapping()
symbols_map.pop_batch(symbols_wo_mapping)
symbols_id_map = symbols_map.convert_to_symbols_ids_map(
to_symbols=model_symbols,
from_symbols=trained_symbols,
)
model_symbols_id_map = symbols_ids_map_to_model_symbols_ids_map(
symbols_id_map,
hparams.n_accents,
n_symbols=hparams.n_symbols,
accents_use_own_symbols=hparams.accents_use_own_symbols)
model_weights = get_symbol_weights(hparams)
map_weights(model_symbols_id_map=model_symbols_id_map,
model_weights=model_weights,
trained_weights=trained_weights,
logger=logger)
not_existing_symbols = model_symbols.get_all_symbols() - symbols_map.keys()
no_mapping = symbols_wo_mapping | not_existing_symbols
if len(no_mapping) > 0:
logger.warning(f"Following symbols were not mapped: {no_mapping}")
else:
logger.info("All symbols were mapped.")
return model_weights
def update_symbols(data: MergedDataset, symbols: SymbolIdDict) -> SymbolIdDict:
new_symbols: Set[str] = {
x
for y in data.items()
for x in symbols.get_symbols(y.serialized_symbol_ids)
}
new_symbol_ids = SymbolIdDict.init_from_symbols_with_pad(
new_symbols, pad_symbol=DEFAULT_PADDING_SYMBOL)
if new_symbol_ids.get_all_symbols() != symbols.get_all_symbols():
for entry in data.items():
original_symbols = symbols.get_symbols(entry.serialized_symbol_ids)
entry.serialized_symbol_ids = new_symbol_ids.get_serialized_ids(
original_symbols)
return new_symbol_ids
def get_shard_size(symbols: SymbolIdDict) -> int:
all_symbols = symbols.get_all_symbols()
count = len(all_symbols)
if DEFAULT_PADDING_SYMBOL in all_symbols:
count -= 1
return count
