# 'r_sample' is the list of out_logits list and 'actions' is the list of output tokens.
# The output tokens are sampled following probabilitis by using chain_sampling.
r_sample, actions = net.decode_chain_sampling(
item_enc,
beg_embedding,
data.MAX_TOKENS,
context[idx],
stop_at_token=end_token)
total_samples += 1
# Omit duplicate action sequence to decrease the computing time and to avoid the case that
# the probability of such kind of duplicate action sequences would be increased redundantly and abnormally.
duplicate_flag = False
if len(action_memory) > 0:
for temp_list in action_memory:
if utils.duplicate(temp_list, actions):
duplicate_flag = True
break
if not duplicate_flag:
action_memory.append(actions)
else:
skipped_samples += 1
continue
# Show what the output action sequence is.
action_tokens = []
for temp_idx in actions:
if temp_idx in rev_emb_dict and rev_emb_dict.get(
temp_idx) != '#END':
action_tokens.append(
str(rev_emb_dict.get(
temp_idx)).upper())
# The output tokens are sampled following probability by using chain_sampling.
actions = action_sequence_list[sample_index]
r_sample = sample_logits_list[sample_index]
else:
r_sample, actions = net.decode_chain_sampling(
item_enc,
beg_embedding,
data.MAX_TOKENS,
context[idx],
stop_at_token=end_token)
# Omit duplicate action sequence to decrease the computing time and to avoid the case that
# the probability of such kind of duplicate action sequences would be increased redundantly and abnormally.
duplicate_flag = False
if len(chain_sampling_action_memory) > 0:
for temp_list in chain_sampling_action_memory:
if utils.duplicate(temp_list, actions):
duplicate_flag = True
break
if not duplicate_flag:
chain_sampling_action_memory.append(actions)
else:
continue
# Show what the output action sequence is.
action_tokens = []
for temp_idx in actions:
if temp_idx in rev_emb_dict and rev_emb_dict.get(
temp_idx) != '#END':
action_tokens.append(
str(rev_emb_dict.get(temp_idx)).upper())
# If the last parameter is false, it means that the 0-1 reward is used to calculate the accuracy.