fix: retain backwards compatability in functions

TTS/tts/utils/synthesis.py

@@ -5,14 +5,18 @@
 from torch import nn
 
 
-def numpy_to_torch(np_array, dtype, device="cpu"):
+def numpy_to_torch(np_array, dtype, cuda=False, device="cpu"):
+    if cuda:
+        device = "cuda"
     if np_array is None:
         return None
     tensor = torch.as_tensor(np_array, dtype=dtype, device=device)
     return tensor
 
 
-def compute_style_mel(style_wav, ap, device="cpu"):
+def compute_style_mel(style_wav, ap, cuda=False, device="cpu"):
+    if cuda:
+        device = "cuda"
     style_mel = torch.FloatTensor(
         ap.melspectrogram(ap.load_wav(style_wav, sr=ap.sample_rate)), device=device,
     ).unsqueeze(0)
@@ -71,14 +75,18 @@ def inv_spectrogram(postnet_output, ap, CONFIG):
     return wav
 
 
-def id_to_torch(aux_id, device="cpu"):
+def id_to_torch(aux_id, cuda=False, device="cpu"):
+    if cuda:
+        device = "cuda"
     if aux_id is not None:
         aux_id = np.asarray(aux_id)
         aux_id = torch.from_numpy(aux_id).to(device)
     return aux_id
 
 
-def embedding_to_torch(d_vector, device="cpu"):
+def embedding_to_torch(d_vector, cuda=False, device="cpu"):
+    if cuda:
+        device = "cuda"
     if d_vector is not None:
         d_vector = np.asarray(d_vector)
         d_vector = torch.from_numpy(d_vector).type(torch.FloatTensor)