bug fix

utils/data.py

@@ -1,7 +1,7 @@
 import numpy as np
 
 
-def pad_data(x, length):
+def _pad_data(x, length):
     _pad = 0
     assert x.ndim == 1
     return np.pad(x, (0, length - x.shape[0]),
@@ -11,7 +11,33 @@ def pad_data(x, length):
 
 def prepare_data(inputs):
     max_len = max((len(x) for x in inputs))
-    return np.stack([pad_data(x, max_len) for x in inputs])
+    return np.stack([_pad_data(x, max_len) for x in inputs])
+
+
+def _pad_tensor(x, length):
+    _pad = 0
+    assert x.ndim == 2
+    x = np.pad(x, [[0, 0], [0, length - x.shape[1]]], mode='constant', constant_values=_pad)
+    return x
+
+def prepare_tensor(inputs, out_steps):
+    max_len = max((x.shape[1] for x in inputs)) + 1 # zero-frame
+    remainder = max_len % out_steps
+    pad_len = max_len + (out_steps - remainder) if remainder > 0 else max_len
+    return np.stack([_pad_tensor(x, pad_len) for x in inputs])
+
+
+def _pad_stop_target(x, length):
+    _pad = 1.
+    assert x.ndim == 1
+    return np.pad(x, (0, length - x.shape[0]), mode='constant', constant_values=_pad)
+
+
+def prepare_stop_target(inputs, out_steps):
+    max_len = max((x.shape[0] for x in inputs)) + 1  # zero-frame
+    remainder = max_len % out_steps
+    pad_len = max_len + (out_steps - remainder) if remainder > 0 else max_len
+    return np.stack([_pad_stop_target(x, pad_len) for x in inputs])
 
 
 def pad_per_step(inputs, pad_len):