shithub: opus

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Properly align LPC with lookahead in data loader

--- a/dnn/training_tf2/dataloader.py

+++ b/dnn/training_tf2/dataloader.py

@@ -13,7 +13,7 @@

     return rc

 class LPCNetLoader(Sequence):

-    def __init__(self, data, features, periods, batch_size, e2e=False):

+    def __init__(self, data, features, periods, batch_size, e2e=False, lookahead=2):

         self.batch_size = batch_size

         self.nb_batches = np.minimum(np.minimum(data.shape[0], features.shape[0]), periods.shape[0])//self.batch_size

         self.data = data[:self.nb_batches*self.batch_size, :]

@@ -20,6 +20,7 @@

         self.features = features[:self.nb_batches*self.batch_size, :]

         self.periods = periods[:self.nb_batches*self.batch_size, :]

         self.e2e = e2e

+        self.lookahead = lookahead

         self.on_epoch_end()

     def on_epoch_end(self):

@@ -34,7 +35,10 @@

         periods = self.periods[self.indices[index*self.batch_size:(index+1)*self.batch_size], :, :]

         outputs = [out_data]

         inputs = [in_data, features, periods]

-        lpc = self.features[self.indices[index*self.batch_size:(index+1)*self.batch_size], 2:-2, -16:]

+        if self.lookahead > 0:

+            lpc = self.features[self.indices[index*self.batch_size:(index+1)*self.batch_size], 4-self.lookahead:-self.lookahead, -16:]

+        else:

+            lpc = self.features[self.indices[index*self.batch_size:(index+1)*self.batch_size], 4:, -16:]

         if self.e2e:

             outputs.append(lpc2rc(lpc))

         else:

--- a/dnn/training_tf2/train_lpcnet.py

+++ b/dnn/training_tf2/train_lpcnet.py

@@ -203,7 +203,7 @@

 model.save_weights('{}_{}_initial.h5'.format(args.output, args.grua_size))

-loader = LPCNetLoader(data, features, periods, batch_size, e2e=flag_e2e)

+loader = LPCNetLoader(data, features, periods, batch_size, e2e=flag_e2e, lookahead=args.lookahead)

 callbacks = [checkpoint, sparsify, grub_sparsify]

 if args.logdir is not None:

-- 

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