def eval_model(ds, states, f_log_prob):
total_ce_sum = 0.0
total_frame_count = 0
for b_idx, batch in enumerate(ds.get_epoch_iterator(), start=1):
reset_state(states)
input_data, input_mask, ivector_data, ivector_mask, target_data, target_mask = batch
n_batch, n_seq, n_feat = input_data.shape
if n_batch < args.batch_size:
continue
input_data = numpy.transpose(input_data, (1, 0, 2))
target_data = numpy.transpose(target_data, (1, 0))
target_mask = numpy.transpose(target_mask, (1, 0))
cost, cost_len = f_log_prob(input_data, target_data, target_mask)
total_ce_sum += cost.sum()
total_frame_count += cost_len.sum()
return total_ce_sum / total_frame_count
def avg_z_1_3d(ds, states, f_debug):
total_ce_sum = 0.0
total_frame_count = 0
z_1_3d_list = []
for b_idx, batch in enumerate(ds.get_epoch_iterator(), start=1):
reset_state(states)
input_data, input_mask, ivector_data, ivector_mask, target_data, target_mask = batch
n_batch, n_seq, n_feat = input_data.shape
if n_batch < args.batch_size:
continue
input_data = numpy.transpose(input_data, (1, 0, 2))
target_data = numpy.transpose(target_data, (1, 0))
target_mask = numpy.transpose(target_mask, (1, 0))
h_rnn_1_3d, h_rnn_2_3d, h_rnn_3_3d, z_1_3d, z_2_3d = \
f_debug(input_data, target_data, target_mask)
z_1_3d_list.append(z_1_3d)
return batch_mean(z_1_3d_list)
tparams = init_tparams_with_restored_value(tparams, args.model)
print('Loading data streams from {}'.format(args.data_path))
sync_data(args)
ds = create_ivector_datastream(args.data_path, args.dataset,
args.batch_size)
epoch_sw = StopWatch()
status_sw = StopWatch()
status_sw.reset()
z_1_3d_list = []
for b_idx, batch in enumerate(ds.get_epoch_iterator(), start=1):
reset_state(states)
input_data, input_mask, ivector_data, ivector_mask, target_data, target_mask = batch
n_batch, n_seq, n_feat = input_data.shape
if n_batch < args.batch_size:
continue
input_data_trans = numpy.transpose(input_data, (1, 0, 2))
_, _, _, z_1_3d, _ = f_debug(input_data_trans)
z_1_3d_trans = numpy.transpose(z_1_3d, (1, 0))
compressed_input_data = compress_batch(input_data, z_1_3d_trans)
compressed_input_mask = compress_batch(input_mask, z_1_3d_trans)
compressed_target_data = compress_batch(target_data, z_1_3d_trans)
compressed_target_mask = compress_batch(target_mask, z_1_3d_trans)