def analyze_results(params, stats, what_stats, aux_names=None, aux_stats=None):
d = {}
for idx, what_stat in enumerate(what_stats):
for idx2, param in enumerate(params):
d[(what_stat, get_p(param))] = stats[idx][idx2]
headers = ['+'] + [what_stat.NAME for what_stat in what_stats]
table = []
for param in params:
row = [get_p(param).name]
for what_stat in what_stats:
row.append(str(d[(what_stat, get_p(param))]))
table.append(row)
print tabulate(table, headers, tablefmt='simple')
##################################################
if aux_names is not None:
print ''
table2 = []
for idx, name in enumerate(AUX_NAMES):
table2.append([name] + aux_stats[idx].tolist())
headers = ['+'] + aux_names
print tabulate(table2, headers, tablefmt='simple')
def analyze_results(params, stats, what_stats, aux_names=None, aux_stats=None):
d = {}
for idx, what_stat in enumerate(what_stats):
for idx2, param in enumerate(params):
d[(what_stat, get_p(param))] = stats[idx][idx2]
headers = ['+'] + [what_stat.NAME for what_stat in what_stats]
table = []
for param in params:
row = [get_p(param).name]
for what_stat in what_stats:
row.append(str(d[(what_stat, get_p(param))]))
table.append(row)
print tabulate(table, headers, tablefmt='simple')
##################################################
if aux_names is not None:
print ''
table2 = []
for idx, name in enumerate(AUX_NAMES):
table2.append([name] + aux_stats[idx].tolist())
headers = ['+'] + aux_names
print tabulate(table2, headers, tablefmt='simple')
def comp_one(self, param, info):
return T.max(T.abs_(get_p(param)))
def comp_one(self, param, info):
return T.mean(T.abs_(info.diff / get_p(param)))
def comp_one(self, param, info):
return info.diff.norm(L=p) / get_p(param).norm(L=p)
def comp_one(self, param, grad=None, diff=None):
return T.max(T.abs_(get_p(param)))
def comp_one(self, param, info):
return T.max(T.abs_(get_p(param)))
def comp_one(self, param, info):
return T.mean(T.abs_(info.diff / get_p(param)))
def comp_one(self, param, info):
return info.diff.norm(L=p) / get_p(param).norm(L=p)
def comp_one(self, param, grad=None, diff=None):
return T.max(T.abs_(get_p(param)))