Remove trailing whitespace in dnn

dnn/README.md

@@ -124,4 +124,3 @@ Suitable training material can be obtained from [Open Speech and Language Resour
 1. [LPCNet: DSP-Boosted Neural Speech Synthesis](https://people.xiph.org/~jm/demo/lpcnet/)
 1. [A Real-Time Wideband Neural Vocoder at 1.6 kb/s Using LPCNet](https://people.xiph.org/~jm/demo/lpcnet_codec/)
 1. Sample model files (check compatibility): https://media.xiph.org/lpcnet/data/
-

dnn/datasets.txt

@@ -171,4 +171,3 @@ The corresponding citations for all these datasets are:
   journal={arXiv preprint arXiv:2104.01497},
   year={2021}
 }
-

dnn/download_model.bat

@@ -9,4 +9,3 @@ if not exist %model% (
 tar -xvzf %model%
 move .\src\*.c .
 move .\src\*.h .
-

dnn/dump_data.c

@@ -260,4 +260,3 @@ int main(int argc, char **argv) {
   lpcnet_encoder_destroy(st);
   return 0;
 }
-

dnn/freq.c

@@ -326,4 +326,3 @@ void apply_window(float *x) {
     x[WINDOW_SIZE - 1 - i] *= half_window[i];
   }
 }
-

dnn/test_vec.c

@@ -126,5 +126,3 @@ int main() {
     int test2 = test_sparse_sgemv_accum16();
     return test1 || test2;
 }
-
-  

dnn/torch/rdovae/fec_encoder.py

@@ -210,4 +210,3 @@ if args.debug_output:
 
         print(f"writing debug output {packet_file[:-4] + f'_torch_batch{batch}_offset{offset}.f32'}")
         test_features_full.tofile(packet_file[:-4] + f'_torch_batch{batch}_offset{offset}.f32')
-

dnn/torch/rdovae/rdovae/dataset.py

@@ -65,4 +65,3 @@ class RDOVAEDataset(torch.utils.data.Dataset):
         rate_lambda = self.lambda_min * np.exp(q_ids.astype(np.float32) / self.denominator).astype(np.float32)
 
         return features, rate_lambda, q_ids
-

dnn/torch/rdovae/rdovae/rdovae.py

@@ -611,4 +611,3 @@ class RDOVAE(nn.Module):
 
         for p in self.statistical_model.parameters():
             p.requires_grad = True
-

dnn/training_tf2/fec_encoder.py

@@ -254,4 +254,3 @@ if args.debug_output:
 
         print(f"writing debug output {packet_file[:-4] + f'_tf_batch{batch}_offset{offset}.f32'}")
         test_features_full.tofile(packet_file[:-4] + f'_tf_batch{batch}_offset{offset}.f32')
-

dnn/training_tf2/lossfuncs.py

@@ -97,4 +97,3 @@ def loss_matchlar():
         loss_lar_diff = tf.square(loss_lar_diff)
         return tf.reduce_mean(loss_lar_diff, axis=-1)
     return loss
-

dnn/training_tf2/rdovae.py

@@ -370,4 +370,3 @@ def new_rdovae_model(nb_used_features=20, nb_bits=17, bunch=4, nb_quant=40, batc
     model.nb_used_features = nb_used_features
 
     return model, encoder, decoder, qembedding
-

dnn/training_tf2/test_lpcnet.py

@@ -118,5 +118,3 @@ for c in range(0, nb_frames):
             #print(mem)
             np.array([np.round(mem)], dtype='int16').tofile(fout)
         skip = 0
-
-