def get_hp_space():
super_space = Model_lop.get_hp_space()
space = {}
space.update(super_space)
return space
def get_hp_space():
super_space = Model_lop.get_hp_space()
space = {
'n_hidden':
hp.choice('n_hidden', [
[
hopt_wrapper.qloguniform_int('n_hidden_1_' + str(i),
log(100), log(5000), 10)
for i in range(1)
],
[
hopt_wrapper.qloguniform_int('n_hidden_2_' + str(i),
log(100), log(5000), 10)
for i in range(2)
],
[
hopt_wrapper.qloguniform_int('n_hidden_3_' + str(i),
log(100), log(5000), 10)
for i in range(3)
],
]),
}
space.update(super_space)
return space
def get_hp_space():
super_space = Model_lop.get_hp_space()
space = {
'num_filter_piano':
list_hopt_fixedSized([(20, 30, 1), (10, 20, 1)],
'num_filter_piano'),
'kernel_size_piano':
list_hopt_fixedSized([(12, 24, 1), (12, 24, 1)],
"kernel_size_piano"),
'num_filter_orch':
list_hopt_fixedSized([(30, 50, 1), (10, 20, 1)],
'num_filter_orch'),
'kernel_size_orch':
list_hopt_fixedSized([(12, 24, 1), (12, 24, 1)],
"kernel_size_orch"),
'embeddings_size':
qloguniform_int("embeddings_size", log(500), log(2000), 10),
'mlp_pred':
list_log_hopt(500, 2000, 10, 1, 3, "mlp_pred"),
'gru_orch':
list_log_hopt(500, 2000, 10, 0, 2, "gru_orch"),
}
space.update(super_space)
return space
def get_hp_space():
super_space = Model_lop.get_hp_space()
space = {'n_hidden': list_log_hopt(500, 2000, 10, 1, 2, "n_hidden")}
space.update(super_space)
return space
def get_hp_space():
super_space = Model_lop.get_hp_space()
space = {
'n_hidden': list_log_hopt(500, 2000, 10, 1, 2, "n_hidden"),
'num_ordering': quniform_int('num_ordering', 5, 5, 1)
}
space.update(super_space)
return space
def get_hp_space():
super_space = Model_lop.get_hp_space()
space = {
'n_hidden': hopt_wrapper.qloguniform_int('n_hidden', log(100), log(5000), 10),
}
space.update(super_space)
return space
def get_hp_space():
super_space = Model_lop.get_hp_space()
space = {
'num_filter_piano': quniform_int('num_filter_piano', 20, 50, 1),
'kernel_size_piano': quniform_int('kernel_size_piano', 8, 16, 1),
'mlp_piano': list_log_hopt(500, 2000, 10, 1, 3, "mlp_piano"),
'mlp_pred': list_log_hopt(500, 2000, 10, 1, 3, "mlp_pred"),
'gru_orch': list_log_hopt(500, 2000, 10, 1, 3, "gru_orch"),
}
space.update(super_space)
return space
def get_hp_space():
super_space = Model_lop.get_hp_space()
space = {
'filter_0': quniform_int('filter_0', 20, 50, 1),
'kernel_0': quniform_int('kernel_0', 8, 16, 1),
'filter_1': quniform_int('filter_1', 20, 50, 1),
'kernel_1': quniform_int('kernel_1', 8, 16, 1),
}
space.update(super_space)
return space
def get_hp_space():
super_space = Model_lop.get_hp_space()
space = {
'n_hidden_embedding': hp.choice('n_hidden_embedding', [
[hopt_wrapper.qloguniform_int('n_hidden_embedding_'+str(i), log(1500), log(3000), 10) for i in range(1)],
[hopt_wrapper.qloguniform_int('n_hidden_embedding_'+str(i), log(1500), log(3000), 10) for i in range(2)],
[hopt_wrapper.qloguniform_int('n_hidden_embedding_'+str(i), log(1500), log(3000), 10) for i in range(3)],
]),
'n_hidden_NADE': hp.choice('n_hidden_NADE', [
[hopt_wrapper.qloguniform_int('n_hidden_NADE_'+str(i), log(1500), log(3000), 10) for i in range(1)],
[hopt_wrapper.qloguniform_int('n_hidden_NADE_'+str(i), log(1500), log(3000), 10) for i in range(2)],
[hopt_wrapper.qloguniform_int('n_hidden_NADE_'+str(i), log(1500), log(3000), 10) for i in range(3)],
]),
'num_ordering': quniform_int('num_ordering', 5, 10, 1)
}
space.update(super_space)
return space
def get_hp_space():
space = Model_lop.get_hp_space()
return space
