mirrors/icefall
1
0
Fork 0
mirror of https://github.com/k2-fsa/icefall.git synced 2025-12-11 06:55:27 +00:00
Code Issues Packages Projects Releases Wiki Activity

from local

Browse Source
This commit is contained in:
dohe0342 2023-04-11 15:46:18 +09:00
parent 1b1a78ff76
commit 3fc6fce04c
3 changed files with 1 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

BIN
egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.optim.py.swp
View File

Binary file not shown.

BIN
egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.prompt_tuning.py.swp
View File

Binary file not shown.

5
egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/prompt_tuning.py
View File

@ -1579,7 +1579,6 @@ def run_adapter(rank, world_size, args, wb=None):
logging.info("Using DDP") logging.info("Using DDP")
model = DDP(model, device_ids=[rank], find_unused_parameters=True) model = DDP(model, device_ids=[rank], find_unused_parameters=True)
'''
adapter_names = [] adapter_names = []
adapter_param = [] adapter_param = []
for n, p in model.named_parameters(): for n, p in model.named_parameters():
@ -1590,14 +1589,12 @@ def run_adapter(rank, world_size, args, wb=None):
p.requires_grad = True p.requires_grad = True
else: else:
p.requires_grad = False p.requires_grad = False
'''
for n, p in model.named_parameters(): for n, p in model.named_parameters():
p.requires_grad = False p.requires_grad = False
prompt = torch.nn.Parameter(torch.randn(50, 512)).to(device) prompt = torch.nn.Parameter(torch.randn(50, 512)).to(device)
'''
optimizer_adapter = ScaledAdam( optimizer_adapter = ScaledAdam(
adapter_param, adapter_param,
lr=params.adapter_lr, lr=params.adapter_lr,
@ -1611,7 +1608,7 @@ def run_adapter(rank, world_size, args, wb=None):
clipping_scale=5.0, clipping_scale=5.0,
parameters_names=['prompt'], parameters_names=['prompt'],
) )
'''
scheduler_adapter = Eden(optimizer_adapter, 10000, 7) #params.lr_batche, params.lr_epochs) scheduler_adapter = Eden(optimizer_adapter, 10000, 7) #params.lr_batche, params.lr_epochs)
optimizer, scheduler = optimizer_adapter, scheduler_adapter optimizer, scheduler = optimizer_adapter, scheduler_adapter