feat: set gpu device explicitly.

- add `use_gpu()`, `use_gpu()` in `__init__.py`

idrlnet/__init__.py

@@ -1,16 +1,43 @@
 import torch
+from .header import logger
 
+GPU_AVAILABLE = False
+GPU_ENABLED = False
 # todo more careful check
-GPU_ENABLED = True
 if torch.cuda.is_available():
     try:
         _ = torch.Tensor([0.0, 0.0]).cuda()
+        logger.info("GPU available")
+        GPU_AVAILABLE = True
+    except:
+        logger.info("GPU not available")
+        GPU_AVAILABLE = False
+else:
+    logger.info("GPU not available")
+    GPU_AVAILABLE = False
+
+
+def use_gpu(device=0):
+    """Use GPU with device `device`.
+
+    Args:
+        device (torch.device or int): selected device.
+    """
+    if GPU_AVAILABLE:
+        try:
+            torch.cuda.set_device(device)
             torch.set_default_tensor_type("torch.cuda.FloatTensor")
-        print("gpu available")
+            logger.info(f"Using GPU device {device}")
+            global GPU_ENABLED
             GPU_ENABLED = True
         except:
-        print("gpu not available")
+            logger.warning("Invalid device ordinal")
-        GPU_ENABLED = False
+
-else:
+
-    print("gpu not available")
+def use_cpu():
-    GPU_ENABLED = False
+    """
+    Use CPU.
+    """
+    if GPU_ENABLED:
+        torch.set_default_tensor_type("torch.FloatTensor")
+    logger.info(f"Using CPU")

idrlnet/shortcut.py

@@ -10,4 +10,4 @@ from idrlnet.callbacks import GradientReceiver
 from idrlnet.receivers import Receiver, Signal
 from idrlnet.variable import Variables, export_var
 from idrlnet.header import logger
-from idrlnet import GPU_ENABLED
+from idrlnet import GPU_AVAILABLE, GPU_ENABLED, use_gpu