dzhwinter
diff --git a/‎HowToDoBenchmark.md‎
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diff --git a/‎fluid/resnet.py‎ ‎fluid/resnet50.py‎fluid/resnet.py renamed to fluid/resnet50.py b/‎fluid/resnet.py‎ ‎fluid/resnet50.py‎fluid/resnet.py renamed to fluid/resnet50.py
diff --git a/‎fluid/understand_sentiment_by_dynrnn.py‎ ‎fluid/stacked_dynamic_lstm.py‎fluid/understand_sentiment_by_dynrnn.py renamed to fluid/stacked_dynamic_lstm.py
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diff --git a/‎fluid/understand_sentiment_dynamic_lstm.py‎
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diff --git a/‎fluid/understand_sentiment_lstm.py‎
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diff --git a/‎tensorflow/resnet.py‎ ‎tensorflow/resnet50.py‎tensorflow/resnet.py renamed to tensorflow/resnet50.py b/‎tensorflow/resnet.py‎ ‎tensorflow/resnet50.py‎tensorflow/resnet.py renamed to tensorflow/resnet50.py
@@ -38,7 +38,7 @@ docker pull tensorflow/tensorflow:1.4.0-gpu
 
 首先需要屏蔽GPU `export CUDA_VISIBLE_DEVICES=`;
 
-Fluid需要关闭OpenMP. 设置`export OMP_NUM_THREADS=1`. 设置Device=CPU, 或者在代码中设置CPUPlace().
+在单机单卡的测试环境中,Fluid需要关闭OpenMP. 设置`export OMP_NUM_THREADS=1`. 设置Device=CPU, 或者在代码中设置CPUPlace().
 TensorFlow需要关闭多线程, 设置 intra_op_parallelism_threads=1, inter_op_parallelism_threads=1.
 运行过程中可以通过, `nvidia-smi`来校验是否有GPU被使用, 下文GPU同理.
 
 
@@ -113,7 +113,7 @@ def gate_common(
     adam = fluid.optimizer.Adam()
     adam.minimize(loss)
 
-    place = fluid.CPUPlace() if args.device == 'CPU' else fluid.GPUPlace(0)
+    place = fluid.CPUPlace() if args.device == 'CPU' else fluid.CUDAPlace(0)
     exe = fluid.Executor(place)
     exe.run(fluid.default_startup_program())