Raise an error when multiple GPUs are in use

User must define the target GPU by `CUDA_VISIBLE_DEVICES` and
use `distribute.py` for multi-gpu training.

TTS/utils/trainer_utils.py

@@ -11,11 +11,15 @@ def is_apex_available():
 
 
 def setup_torch_training_env(cudnn_enable, cudnn_benchmark):
+    num_gpus = torch.cuda.device_count()
+    if num_gpus > 1:
+        raise RuntimeError(
+            f" [!] {num_gpus} active GPUs. Define the target GPU by `CUDA_VISIBLE_DEVICES`. For multi-gpu training use `TTS/bin/distribute.py`."
+        )
     torch.backends.cudnn.enabled = cudnn_enable
     torch.backends.cudnn.benchmark = cudnn_benchmark
     torch.manual_seed(54321)
     use_cuda = torch.cuda.is_available()
-    num_gpus = torch.cuda.device_count()
     print(" > Using CUDA: ", use_cuda)
     print(" > Number of GPUs: ", num_gpus)
     return use_cuda, num_gpus