def select(metricname, opt):
if 'e_recall' in metricname:
k = int(metricname.split('@')[-1])
return e_recall.Metric(k)
elif metricname == 'nmi':
return nmi.Metric()
elif metricname == 'mAP':
return mAP.Metric()
elif metricname == 'mAP_c':
return mAP_c.Metric()
elif metricname == 'mAP_lim':
return mAP_lim.Metric()
elif metricname == 'mAP_1000':
return mAP_1000.Metric()
elif metricname == 'f1':
return f1.Metric()
elif 'dists' in metricname:
mode = metricname.split('@')[-1]
return dists.Metric(mode)
elif 'rho_spectrum' in metricname:
mode = int(metricname.split('@')[-1])
embed_dim = opt.rho_spectrum_embed_dim
return rho_spectrum.Metric(embed_dim, mode=mode, opt=opt)
else:
raise NotImplementedError(
"Metric {} not available!".format(metricname))
def select(metricname, opt):
#### Metrics based on euclidean distances
if 'e_recall' in metricname:
k = int(metricname.split('@')[-1])
return e_recall.Metric(k)
elif metricname=='nmi':
return nmi.Metric()
elif metricname=='mAP':
return mAP.Metric()
elif metricname=='mAP_c':
return mAP_c.Metric()
elif metricname=='mAP_lim':
return mAP_lim.Metric()
elif metricname=='mAP_1000':
return mAP_1000.Metric()
elif metricname=='f1':
return f1.Metric()
#### Metrics based on cosine similarity
elif 'c_recall' in metricname:
k = int(metricname.split('@')[-1])
return c_recall.Metric(k)
elif metricname=='c_nmi':
return c_nmi.Metric()
elif metricname=='c_mAP':
return c_mAP.Metric()
elif metricname=='c_mAP_c':
return c_mAP_c.Metric()
elif metricname=='c_mAP_lim':
return c_mAP_lim.Metric()
elif metricname=='c_mAP_1000':
return c_mAP_1000.Metric()
elif metricname=='c_f1':
return c_f1.Metric()
#### Generic Embedding space metrics
elif 'dists' in metricname:
mode = metricname.split('@')[-1]
return dists.Metric(mode)
elif 'rho_spectrum' in metricname:
mode = int(metricname.split('@')[-1])
embed_dim = opt.rho_spectrum_embed_dim
return rho_spectrum.Metric(embed_dim, mode=mode, opt=opt)
else:
raise NotImplementedError("Metric {} not available!".format(metricname))
def select(metricname):
if 'e_recall' in metricname:
k = int(metricname.split('@')[-1])
return e_recall.Metric(k)
elif 'a_recall' in metricname:
k = int(metricname.split('@')[-1])
return a_recall.Metric(k)
elif metricname == 'nmi':
return nmi.Metric()
elif metricname == 'mAP_c':
return mAP_c.Metric()
elif metricname == 'f1':
return f1.Metric()
elif 'dists' in metricname:
mode = metricname.split('@')[-1]
return dists.Metric(mode)
else:
raise NotImplementedError(
"Metric {} not available!".format(metricname))