Merge pull request #314 from D-X-Y/fshare

(1) Fix /0 bug in double_ensemble, (2) remove _default_uri for R/expm, (3) support model size in pytorch models

qlib/contrib/model/pytorch_gats_ts.py

@@ -24,6 +24,7 @@ import torch.optim as optim
 from torch.utils.data import DataLoader
 from torch.utils.data import Sampler
 
+from .pytorch_utils import count_parameters
 from ...model.base import Model
 from ...data.dataset import DatasetH
 from ...data.dataset.handler import DataHandlerLP
@@ -62,8 +63,8 @@ class GATs(Model):
         the evaluate metric used in early stop
     optimizer : str
         optimizer name
-    GPU : str
-        the GPU ID(s) used for training
+    GPU : int
+        the GPU ID used for training
     """
 
     def __init__(
@@ -104,7 +105,7 @@ class GATs(Model):
         self.base_model = base_model
         self.with_pretrain = with_pretrain
         self.model_path = model_path
-        self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu")
+        self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() and GPU >= 0 else "cpu")
         self.n_jobs = n_jobs
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
@@ -157,6 +158,9 @@ class GATs(Model):
             dropout=self.dropout,
             base_model=self.base_model,
         )
+        self.logger.info("model:\n{:}".format(self.GAT_model))
+        self.logger.info("model size: {:.4f} MB".format(count_parameters(self.GAT_model)))
+
         if optimizer.lower() == "adam":
             self.train_optimizer = optim.Adam(self.GAT_model.parameters(), lr=self.lr)
         elif optimizer.lower() == "gd":
@@ -245,7 +249,6 @@ class GATs(Model):
         self,
         dataset,
         evals_result=dict(),
-        verbose=True,
         save_path=None,
     ):