def check_fn(*args, **kwargs):
if not to_check_train_step():
return fn(*args, **kwargs)
net = args[0] # first arg self
# get pre-update parameters to compare
pre_params = [param.clone() for param in net.parameters()]
# run train_step, get loss
loss = fn(*args, **kwargs)
assert not torch.isnan(loss).any(), loss
# get post-update parameters to compare
post_params = [param.clone() for param in net.parameters()]
if loss == 0.0:
# if loss is 0, there should be no updates
# TODO if without momentum, parameters should not change too
for p_name, param in net.named_parameters():
assert param.grad.norm() == 0
else:
# check parameter updates
try:
assert not all(
torch.equal(w1, w2)
for w1, w2 in zip(pre_params, post_params)
), f'Model parameter is not updated in train_step(), check if your tensor is detached from graph. Loss: {loss:g}'
logger.info(
f'Model parameter is updated in train_step(). Loss: {loss: g}'
)
except Exception as e:
logger.error(e)
if os.environ.get('PY_ENV') == 'test':
# raise error if in unit test
raise (e)
# check grad norms
min_norm, max_norm = 0.0, 1e5
for p_name, param in net.named_parameters():
try:
grad_norm = param.grad.norm()
assert min_norm < grad_norm < max_norm, f'Gradient norm for {p_name} is {grad_norm:g}, fails the extreme value check {min_norm} < grad_norm < {max_norm}. Loss: {loss:g}. Check your network and loss computation.'
except Exception as e:
logger.warning(e)
logger.info(f'Gradient norms passed value check.')
logger.debug('Passed network parameter update check.')
# store grad norms for debugging
net.store_grad_norms()
return loss
def _transform_sysact_in(cls, action):
new_action = {}
if not isinstance(action, dict):
logger.warning(f'illegal da: {action}')
return new_action
for act in action.keys():
if not isinstance(act, str) or '-' not in act:
logger.warning(f'illegal act: {act}')
continue
if 'general' not in act:
(dom, intent) = act.lower().split('-')
if dom in REF_SYS_DA_M.keys():
new_list = []
for pairs in action[act]:
if (not isinstance(pairs, list) and not isinstance(pairs, tuple)) or\
(len(pairs) < 2) or\
(not isinstance(pairs[0], str) or (not isinstance(pairs[1], str) and not isinstance(pairs[1], int))):
logger.warning(f'illegal pairs: {pairs}')
continue
if REF_SYS_DA_M[dom].get(pairs[0].lower(), None) is not None:
new_list.append([REF_SYS_DA_M[dom][pairs[0].lower()], cls._normalize_value(dom, intent, REF_SYS_DA_M[dom][pairs[0].lower()], pairs[1])])
if len(new_list) > 0:
new_action[act.lower()] = new_list
else:
new_action[act.lower()] = action[act]
return new_action
import os
import colorlover as cl
import pydash as ps
# The data visualization module
# Defines plotting methods for analysis
from plotly import graph_objs as go, io as pio, tools
from plotly.offline import init_notebook_mode, iplot
from convlab.lib import logger, util
logger = logger.get_logger(__name__)
# warn orca failure only once
orca_warn_once = ps.once(lambda e: logger.warning(
f'Failed to generate graph. Run retro-analysis to generate graphs later.'))
if util.is_jupyter():
init_notebook_mode(connected=True)
def create_label(y_col,
x_col,
title=None,
y_title=None,
x_title=None,
legend_name=None):
'''Create label dict for go.Layout with smart resolution'''
legend_name = legend_name or y_col
y_col_list, x_col_list, legend_name_list = ps.map_(
[y_col, x_col, legend_name], util.cast_list)
y_title = str(y_title or ','.join(y_col_list))
def update_booking(self, diaact, slot_vals, goal: Goal):
"""
Handel Book-XXX
:param diaact: Dial-Act
:param slot_vals: slot value pairs
:param goal: Goal
:return: True:user want to close the session. False:session is continue
"""
_, intent = diaact.split('-')
domain = self.cur_domain
if domain not in goal.domains:
return False
g_reqt = goal.domain_goals[domain].get('reqt', dict({}))
g_info = goal.domain_goals[domain].get('info', dict({}))
g_fail_info = goal.domain_goals[domain].get('fail_info', dict({}))
g_book = goal.domain_goals[domain].get('book', dict({}))
g_fail_book = goal.domain_goals[domain].get('fail_book', dict({}))
if intent in ['book', 'inform']:
info_right = True
for [slot, value] in slot_vals:
if slot == 'time':
if domain in ['train', 'restaurant']:
slot = 'duration' if domain == 'train' else 'time'
else:
logger.warning(f'illegal booking slot: {slot}, domain: {domain}')
continue
if slot in g_reqt:
if not self._check_reqt_info(domain):
self._remove_item(domain + '-request', slot)
if value in NOT_SURE_VALS:
g_reqt[slot] = '\"' + value + '\"'
else:
g_reqt[slot] = value
elif slot in g_fail_info and value != g_fail_info[slot]:
self._push_item(domain + '-inform', slot, g_fail_info[slot])
info_right = False
elif len(g_fail_info) <= 0 and slot in g_info and check_constraint(slot, g_info[slot], value):
self._push_item(domain + '-inform', slot, g_info[slot])
info_right = False
elif slot in g_fail_book and value != g_fail_book[slot]:
self._push_item(domain + '-inform', slot, g_fail_book[slot])
info_right = False
elif len(g_fail_book) <= 0 and slot in g_book and value != g_book[slot]:
self._push_item(domain + '-inform', slot, g_book[slot])
info_right = False
else:
pass
if intent == 'book' and info_right:
# booked ok
if 'booked' in goal.domain_goals[domain]:
goal.domain_goals[domain]['booked'] = DEF_VAL_BOOKED
self._push_item('general-thank')
elif intent in ['nobook']:
if len(g_fail_book) > 0:
# Discard fail_book data and update the book data to the stack
for slot in g_book.keys():
if (slot not in g_fail_book) or (slot in g_fail_book and g_fail_book[slot] != g_book[slot]):
self._push_item(domain + '-inform', slot, g_book[slot])
# change fail_info name
goal.domain_goals[domain]['fail_book_fail'] = goal.domain_goals[domain].pop('fail_book')
elif 'booked' in goal.domain_goals[domain].keys():
self.close_session()
return True
elif intent in ['request']:
for [slot, _] in slot_vals:
if slot == 'time':
if domain in ['train', 'restaurant']:
slot = 'duration' if domain == 'train' else 'time'
else:
logger.warning('illegal booking slot: %s, slot: %s domain' % (slot, domain))
continue
if slot in g_reqt:
pass
elif slot in g_fail_info:
self._push_item(domain + '-inform', slot, g_fail_info[slot])
elif len(g_fail_info) <= 0 and slot in g_info:
self._push_item(domain + '-inform', slot, g_info[slot])
elif slot in g_fail_book:
self._push_item(domain + '-inform', slot, g_fail_book[slot])
elif len(g_fail_book) <= 0 and slot in g_book:
self._push_item(domain + '-inform', slot, g_book[slot])
else:
if domain == 'taxi' and (slot == 'destination' or slot == 'departure'):
places = [dom for dom in goal.domains[: goal.domains.index('taxi')] if
'address' in goal.domain_goals[dom]['reqt']]
if len(places) >= 1 and slot == 'destination' and \
goal.domain_goals[places[-1]]['reqt']['address'] not in NOT_SURE_VALS:
self._push_item(domain + '-inform', slot, goal.domain_goals[places[-1]]['reqt']['address'])
elif len(places) >= 2 and slot == 'departure' and \
goal.domain_goals[places[-2]]['reqt']['address'] not in NOT_SURE_VALS:
self._push_item(domain + '-inform', slot, goal.domain_goals[places[-2]]['reqt']['address'])
elif random.random() < 0.5:
self._push_item(domain + '-inform', slot, DEF_VAL_DNC)
elif random.random() < 0.5:
self._push_item(domain + '-inform', slot, DEF_VAL_DNC)
return False