def inject_retrieval_code(net_dict, rec_layer_name, layers, dropout):
"""
Injects some retrieval code into the config
:param dict[str] net_dict:
:param str rec_layer_name: name of rec layer
:param list[str] layers: layers in rec layer to extract
:param float|None dropout: to override, if given
:return: net_dict
:rtype: dict[str]
"""
assert config is not None
assert rec_layer_name in net_dict
assert net_dict[rec_layer_name]["class"] == "rec"
for l in layers:
assert l in net_dict[rec_layer_name]['unit'], "layer %r not found" % l
new_layers_descr = net_dict.copy() # actually better would be deepcopy...
for sub_layer in layers:
# assert that sub_layer inside subnet is a output-layer
new_layers_descr[rec_layer_name]['unit'][sub_layer]["is_output_layer"] = True
if dropout is not None:
deep_update_dict_values(net_dict, "dropout", dropout)
deep_update_dict_values(net_dict, "rec_weight_dropout", dropout)
return new_layers_descr
def inject_retrieval_code(net_dict, rec_layer_name, layers, dropout, args):
"""
Injects some retrieval code into the config
:param dict[str] net_dict:
:param str rec_layer_name: name of rec layer
:param list[str] layers: layers in rec layer to extract
:param float|None dropout: to override, if given
:return: net_dict
:rtype: dict[str]
"""
assert config is not None
assert rec_layer_name in net_dict
assert net_dict[rec_layer_name]["class"] == "rec"
new_layers_descr = net_dict.copy() # actually better would be deepcopy...
if args.instead_save_encoder_decoder:
new_layers_descr["encoder"]["is_output_layer"] = True
new_layers_descr[rec_layer_name]['unit']["decoder"][
"is_output_layer"] = True
else:
for l in layers:
assert l in net_dict[rec_layer_name][
'unit'], "layer %r not found" % l
for sub_layer in layers:
# assert that sub_layer inside subnet is a output-layer
new_layers_descr[rec_layer_name]['unit'][sub_layer][
"is_output_layer"] = True
if dropout is not None:
deep_update_dict_values(net_dict, "dropout", dropout)
deep_update_dict_values(net_dict, "rec_weight_dropout", dropout)
if args.hmm_fac_fo:
# hmm fac layer
new_layers_descr[rec_layer_name]['unit']["output_prob"][
"attention_location"] = args.dump_dir
new_layers_descr[rec_layer_name][
"optimize_move_layers_out"] = False
if args.encoder_sa:
# Encoder self attention
for l in net_dict:
if "enc" in l:
if net_dict[l]["class"] == "self_attention":
net_dict[l]["attention_location"] = args.dump_dir
return new_layers_descr