num_hidden_proj=num_hidden_proj)
data_names = [x[0] for x in data_test.provide_data]
label_names = ['softmax_label']
module = mx.mod.Module(sym,
context=contexts,
data_names=data_names,
label_names=label_names)
# set the parameters
module.bind(data_shapes=data_test.provide_data,
label_shapes=None,
for_training=False)
module.set_params(arg_params=arg_params, aux_params=aux_params)
#kaldiWriter = KaldiWriteOut(None, out_file)
#kaldiWriter.open_or_fd()
kaldiWriter = KaldiWriteOut(out_dir + "/feats.scp", out_dir + "/feats.ark")
kaldiWriter.open()
for preds, i_batch, batch in module.iter_predict(data_test):
label = batch.label[0].asnumpy().astype('int32')
posteriors = preds[0].asnumpy().astype('float32')
# copy over states
if decoding_method == METHOD_BUCKETING:
for (ind, utt) in enumerate(batch.utt_id):
if utt != "GAP_UTT":
posteriors = np.log(posteriors[:label[0][0], 1:] +
1e-20) - np.log(
data_train.label_mean).T
kaldiWriter.write(utt, posteriors)
elif decoding_method == METHOD_SIMPLE:
for (ind, utt) in enumerate(batch.utt_id):
if utt != "GAP_UTT":
num_label=label_dim,
output_states=True,
num_hidden_proj=num_hidden_proj)
data_names = [x[0] for x in data_test.provide_data]
label_names = ['softmax_label']
module = mx.mod.Module(sym,
context=contexts,
data_names=data_names,
label_names=label_names)
# set the parameters
module.bind(data_shapes=data_test.provide_data,
label_shapes=None,
for_training=False)
module.set_params(arg_params=arg_params, aux_params=aux_params)
kaldiWriter = KaldiWriteOut(None, out_file)
kaldiWriter.open_or_fd()
for preds, i_batch, batch in module.iter_predict(data_test):
#pred_label = np.array(preds[0].asnumpy().argmax(axis=1))
label = batch.label[0].asnumpy().astype('int32')
posteriors = preds[0].asnumpy().astype('float32')[0]
#print np.sum(posteriors[1][:])
# copy over states
if decoding_method == METHOD_BUCKETING:
for (ind, utt) in enumerate(batch.utt_id):
if utt != "GAP_UTT":
#print sum(posteriors[0,:])
posteriors = np.log(posteriors[:label[0][0], 1:] +
1e-20) - np.log(
data_train.label_mean).T
