Skip to content

Fix pre-norm weight conversion for nmt #1723

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

Fix pre-norm weight conversion for nmt #1723

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 9 additions & 3 deletions examples/enc_dec/convert_checkpoint.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -320,8 +320,8 @@ def parse_nmt_config(args, model):
config["encoder"][key] = f"{val}"
config["encoder"]["weight_data_type"] = args.weight_data_type
config["encoder"]["q_scaling"] = '1'
# NMT doesn't have final layernorm
config['encoder']['has_model_final_layernorm'] = 'false'
# NMT has final layernorm for pre-norm model architecture.
config['encoder']['has_model_final_layernorm'] = config['encoder']['encoder_normalize_before']
config['encoder']['vocab_size'] = str(len(model.src_dict)) # fairseq naming

config['decoder'] = dict()
Expand All @@ -330,7 +330,7 @@ def parse_nmt_config(args, model):
config["decoder"]["weight_data_type"] = args.weight_data_type
config["decoder"]["q_scaling"] = '1'
config["decoder"]["rescale_before_lm_head"] = 'false'
config['decoder']['has_model_final_layernorm'] = 'false'
config['decoder']['has_model_final_layernorm'] = config['decoder']['decoder_normalize_before'] and not config['decoder'].getboolean('no_decoder_final_norm', False)
config['decoder']['vocab_size'] = str(len(model.tgt_dict)) # fairseq naming

config["structure"] = dict()
Expand Down Expand Up @@ -579,6 +579,12 @@ def get_attn_module_name(component, layer, attn_type):
mapping.tp_rank,
dim=0), (config.vocab_size // mapping.tp_size, hidden_size))

if config.has_model_final_layernorm:
weights['final_layernorm.weight'] = params[
f'{hf_param_prefix}.layer_norm.weight'].clone()
weights['final_layernorm.bias'] = params[
f'{hf_param_prefix}.layer_norm.bias'].clone()

return weights


Expand Down