Replace get_device (#231)

* use get_device_from_id * replace all get_device
chainer · May 7, 2018 · f45b5e3 · f45b5e3
1 parent 0330ffb
commit f45b5e3
Show file tree

Hide file tree

Showing 17 changed files with 20 additions and 20 deletions.
diff --git a/docs/source/tutorial/step1_communicators_optimizers.rst b/docs/source/tutorial/step1_communicators_optimizers.rst
@@ -25,12 +25,12 @@ Therefore, it is often convenient to use the ``intra_rank``-th GPU.
 
 The following line of code is found in the original MNIST example::
 
-  chainer.cuda.get_device(args.gpu).use()
+  chainer.cuda.get_device_from_id(args.gpu).use()
 
 which we modify as follows::
 
   device = comm.intra_rank
-  chainer.cuda.get_device(device).use()
+  chainer.cuda.get_device_from_id(device).use()
 
 
 Creating a Multi-Node Optimizer

diff --git a/examples/imagenet/train_imagenet.py b/examples/imagenet/train_imagenet.py
@@ -149,7 +149,7 @@ def main():
         print('Load model from', args.initmodel)
         chainer.serializers.load_npz(args.initmodel, model)
 
-    chainer.cuda.get_device(device).use()  # Make the GPU current
+    chainer.cuda.get_device_from_id(device).use()  # Make the GPU current
     model.to_gpu()
 
     # Split and distribute the dataset. Only worker 0 loads the whole dataset.

diff --git a/examples/mnist/train_mnist.py b/examples/mnist/train_mnist.py
@@ -74,7 +74,7 @@ def main():
 
     model = L.Classifier(MLP(args.unit, 10))
     if device >= 0:
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
         model.to_gpu()
 
     # Create a multi node optimizer from a standard Chainer optimizer.

diff --git a/examples/mnist/train_mnist_checkpoint.py b/examples/mnist/train_mnist_checkpoint.py
@@ -77,7 +77,7 @@ def main():
 
     model = L.Classifier(MLP(args.unit, 10))
     if device >= 0:
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
         model.to_gpu()
 
     # Create a multi node optimizer from a standard Chainer optimizer.

diff --git a/examples/mnist/train_mnist_dual_parallel.py b/examples/mnist/train_mnist_dual_parallel.py
@@ -110,7 +110,7 @@ def main():
         model = MLP1(model_comm, args.unit, 10)
 
     if device >= 0:
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
         model.to_gpu()
 
     optimizer = chainermn.create_multi_node_optimizer(

diff --git a/examples/mnist/train_mnist_model_parallel.py b/examples/mnist/train_mnist_model_parallel.py
@@ -103,7 +103,7 @@ def main():
         model = MLP1(comm, args.unit, 10)
 
     if device >= 0:
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
         model.to_gpu()
 
     optimizer = chainer.optimizers.Adam()

diff --git a/examples/seq2seq/seq2seq.py b/examples/seq2seq/seq2seq.py
@@ -427,7 +427,7 @@ def main():
     model = Seq2seq(3, len(source_ids), len(target_ids), args.unit)
 
     if dev >= 0:
-        chainer.cuda.get_device(dev).use()
+        chainer.cuda.get_device_from_id(dev).use()
         model.to_gpu(dev)
 
     # determine the stop trigger

diff --git a/examples/seq2seq/seq2seq_mp1.py b/examples/seq2seq/seq2seq_mp1.py
@@ -455,7 +455,7 @@ def main():
             comm, n_lstm_layers, len(source_ids), len(target_ids), args.unit)
 
     if dev >= 0:
-        chainer.cuda.get_device(dev).use()
+        chainer.cuda.get_device_from_id(dev).use()
         model.to_gpu(dev)
 
     # determine the stop trigger

diff --git a/tests/chainermn_tests/communicator_tests/test_communicator.py b/tests/chainermn_tests/communicator_tests/test_communicator.py
@@ -117,7 +117,7 @@ def create_communicator(param, use_gpu):
         communicator = param.communicator_class(mpi_comm)
 
     if use_gpu:
-        chainer.cuda.get_device(communicator.intra_rank).use()
+        chainer.cuda.get_device_from_id(communicator.intra_rank).use()
 
     return communicator
 

diff --git a/tests/chainermn_tests/datasets_tests/test_mnist.py b/tests/chainermn_tests/datasets_tests/test_mnist.py
@@ -37,7 +37,7 @@ def check_mnist(gpu, display_log=True):
     comm = chainermn.create_communicator('naive')
     if gpu:
         device = comm.intra_rank
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
     else:
         device = -1
 

diff --git a/tests/chainermn_tests/extensions_tests/test_allreduce_persistent.py b/tests/chainermn_tests/extensions_tests/test_allreduce_persistent.py
@@ -44,7 +44,7 @@ def test_allreduce_persistent_cpu(self):
     def test_allreduce_persistent_gpu(self):
         comm = chainermn.create_communicator('hierarchical')
         device = comm.intra_rank
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
 
         model = ExampleModel()
         model.to_gpu()

diff --git a/tests/chainermn_tests/functions_tests/test_collective_communication.py b/tests/chainermn_tests/functions_tests/test_collective_communication.py
@@ -17,7 +17,7 @@ def setup(self, gpu):
         if gpu:
             self.communicator = chainermn.create_communicator('hierarchical')
             self.device = self.communicator.intra_rank
-            chainer.cuda.get_device(self.device).use()
+            chainer.cuda.get_device_from_id(self.device).use()
         else:
             self.communicator = chainermn.create_communicator('naive')
             self.device = -1

diff --git a/tests/chainermn_tests/functions_tests/test_point_to_point_communication.py b/tests/chainermn_tests/functions_tests/test_point_to_point_communication.py
@@ -19,7 +19,7 @@ def setup(self, gpu):
         if self.gpu:
             self.communicator = chainermn.create_communicator('hierarchical')
             device = self.communicator.intra_rank
-            chainer.cuda.get_device(device).use()
+            chainer.cuda.get_device_from_id(device).use()
         else:
             self.communicator = chainermn.create_communicator('naive')
             device = -1

diff --git a/tests/chainermn_tests/links_tests/test_multi_node_chain_list.py b/tests/chainermn_tests/links_tests/test_multi_node_chain_list.py
@@ -205,7 +205,7 @@ def __init__(self, comm, size, rank_parent):
 def create_communicator(gpu):
     if gpu:
         communicator = chainermn.create_communicator('hierarchical')
-        chainer.cuda.get_device(communicator.intra_rank).use()
+        chainer.cuda.get_device_from_id(communicator.intra_rank).use()
     else:
         communicator = chainermn.create_communicator('naive')
 

diff --git a/tests/chainermn_tests/links_tests/test_n_step_rnn.py b/tests/chainermn_tests/links_tests/test_n_step_rnn.py
@@ -43,7 +43,7 @@ class TestNStepRNN(unittest.TestCase):
     def setup(self, gpu):
         if gpu:
             self.communicator = chainermn.create_communicator('hierarchical')
-            chainer.cuda.get_device(self.communicator.intra_rank).use()
+            chainer.cuda.get_device_from_id(self.communicator.intra_rank).use()
         else:
             self.communicator = chainermn.create_communicator('naive')
 

diff --git a/tests/chainermn_tests/optimizer_tests/test_double_buffering_optimizer.py b/tests/chainermn_tests/optimizer_tests/test_double_buffering_optimizer.py
@@ -26,7 +26,7 @@ def setup_gpu(self, device=None):
             pytest.skip('This test requires NCCL version >= 2.0')
         self.comm = chainermn.create_communicator('pure_nccl')
         device = self.comm.intra_rank
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
         self.target = ExampleModel()
         self.target.to_gpu()
         self.target.a.W.data[:] = self.comm.rank
@@ -103,7 +103,7 @@ def setup_gpu(self, device=None):
             pytest.skip('This test requires NCCL version >= 2.0')
         self.comm = chainermn.create_communicator('pure_nccl')
         device = self.comm.intra_rank
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
         self.target = DynamicExampleModel()
         self.target.to_gpu()
         self.target.a.W.data[:] = self.comm.rank

diff --git a/tests/chainermn_tests/optimizer_tests/test_multi_node_optimizer.py b/tests/chainermn_tests/optimizer_tests/test_multi_node_optimizer.py
@@ -34,7 +34,7 @@ def setup_cpu(self):
     def setup_gpu(self, device=None):
         self.comm = chainermn.create_communicator('hierarchical')
         device = self.comm.intra_rank
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
         self.target = ExampleModel()
         self.target.to_gpu()
         self.target.a.W.data[:] = self.comm.rank
@@ -128,7 +128,7 @@ def setup_cpu(self):
     def setup_gpu(self, device=None):
         self.comm = chainermn.create_communicator('hierarchical')
         device = self.comm.intra_rank
-        chainer.cuda.get_device(device).use()
+        chainer.cuda.get_device_from_id(device).use()
         self.target = DynamicExampleModel()
         self.target.to_gpu()
         self.target.a.W.data[:] = self.comm.rank