Use OneTimeLogger and tweak informational message

deeplearning4j · Sep 14, 2017 · 87e8fac · 87e8fac
1 parent 710dc12
commit 87e8fac
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Showing 5 changed files with 20 additions and 10 deletions.
diff --git a/...earning4j-nn/src/main/java/org/deeplearning4j/nn/layers/convolution/ConvolutionLayer.java b/...earning4j-nn/src/main/java/org/deeplearning4j/nn/layers/convolution/ConvolutionLayer.java
@@ -29,6 +29,7 @@
 import org.deeplearning4j.nn.layers.BaseLayer;
 import org.deeplearning4j.nn.params.ConvolutionParamInitializer;
 import org.deeplearning4j.util.ConvolutionUtils;
+import org.deeplearning4j.util.OneTimeLogger;
 import org.nd4j.linalg.activations.IActivation;
 import org.nd4j.linalg.api.memory.MemoryWorkspace;
 import org.nd4j.linalg.api.ndarray.INDArray;
@@ -84,8 +85,9 @@ void initializeHelper() {
             } else {
                 Properties p = Nd4j.getExecutioner().getEnvironmentInformation();
                 if (p.getProperty("backend").equals("CUDA")) {
-                    log.info("Consider using cuDNN by including the deeplearning4j-cuda module. "
-                            + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
+                    OneTimeLogger.info(log, "cuDNN not found: "
+                                    + "use cuDNN for better GPU performance by including the deeplearning4j-cuda module. "
+                                    + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
                 }
             }
         }

diff --git a/.../src/main/java/org/deeplearning4j/nn/layers/convolution/subsampling/SubsamplingLayer.java b/.../src/main/java/org/deeplearning4j/nn/layers/convolution/subsampling/SubsamplingLayer.java
@@ -28,6 +28,7 @@
 import org.deeplearning4j.nn.gradient.Gradient;
 import org.deeplearning4j.nn.layers.AbstractLayer;
 import org.deeplearning4j.util.ConvolutionUtils;
+import org.deeplearning4j.util.OneTimeLogger;
 import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.api.ops.impl.transforms.IsMax;
 import org.nd4j.linalg.api.ops.impl.transforms.convolution.Pooling2D;
@@ -81,8 +82,9 @@ void initializeHelper() {
             } else {
                 Properties p = Nd4j.getExecutioner().getEnvironmentInformation();
                 if (p.getProperty("backend").equals("CUDA")) {
-                    log.info("Consider using cuDNN by including the deeplearning4j-cuda module. "
-                            + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
+                    OneTimeLogger.info(log, "cuDNN not found: "
+                                    + "use cuDNN for better GPU performance by including the deeplearning4j-cuda module. "
+                                    + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
                 }
             }
         }

diff --git a/...ing4j-nn/src/main/java/org/deeplearning4j/nn/layers/normalization/BatchNormalization.java b/...ing4j-nn/src/main/java/org/deeplearning4j/nn/layers/normalization/BatchNormalization.java
@@ -9,6 +9,7 @@
 import org.deeplearning4j.nn.layers.BaseLayer;
 import org.deeplearning4j.nn.params.BatchNormalizationParamInitializer;
 import org.deeplearning4j.optimize.api.IterationListener;
+import org.deeplearning4j.util.OneTimeLogger;
 import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.api.ops.impl.broadcast.BroadcastAddOp;
 import org.nd4j.linalg.api.ops.impl.broadcast.BroadcastDivOp;
@@ -65,8 +66,9 @@ void initializeHelper() {
             } else {
                 Properties p = Nd4j.getExecutioner().getEnvironmentInformation();
                 if (p.getProperty("backend").equals("CUDA")) {
-                    log.info("Consider using cuDNN by including the deeplearning4j-cuda module. "
-                            + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
+                    OneTimeLogger.info(log, "cuDNN not found: "
+                                    + "use cuDNN for better GPU performance by including the deeplearning4j-cuda module. "
+                                    + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
                 }
             }
         }

diff --git a/.../src/main/java/org/deeplearning4j/nn/layers/normalization/LocalResponseNormalization.java b/.../src/main/java/org/deeplearning4j/nn/layers/normalization/LocalResponseNormalization.java
@@ -6,6 +6,7 @@
 import org.deeplearning4j.nn.gradient.Gradient;
 import org.deeplearning4j.nn.graph.ComputationGraph;
 import org.deeplearning4j.nn.layers.AbstractLayer;
+import org.deeplearning4j.util.OneTimeLogger;
 import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.factory.Nd4j;
 import org.nd4j.linalg.indexing.INDArrayIndex;
@@ -87,8 +88,9 @@ void initializeHelper() {
             } else {
                 Properties p = Nd4j.getExecutioner().getEnvironmentInformation();
                 if (p.getProperty("backend").equals("CUDA")) {
-                    log.info("Consider using cuDNN by including the deeplearning4j-cuda module. "
-                            + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
+                    OneTimeLogger.info(log, "cuDNN not found: "
+                                    + "use cuDNN for better GPU performance by including the deeplearning4j-cuda module. "
+                                    + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
                 }
             }
         }

diff --git a/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/layers/recurrent/LSTM.java b/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/layers/recurrent/LSTM.java
@@ -26,6 +26,7 @@
 import org.deeplearning4j.nn.gradient.Gradient;
 import org.deeplearning4j.nn.graph.ComputationGraph;
 import org.deeplearning4j.nn.params.LSTMParamInitializer;
+import org.deeplearning4j.util.OneTimeLogger;
 import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.factory.Nd4j;
 import org.nd4j.linalg.primitives.Pair;
@@ -74,8 +75,9 @@ void initializeHelper() {
             } else {
                 Properties p = Nd4j.getExecutioner().getEnvironmentInformation();
                 if (p.getProperty("backend").equals("CUDA")) {
-                    log.info("Consider using cuDNN by including the deeplearning4j-cuda module. "
-                            + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
+                    OneTimeLogger.info(log, "cuDNN not found: "
+                                    + "use cuDNN for better GPU performance by including the deeplearning4j-cuda module. "
+                                    + "For more information, please refer to: https://deeplearning4j.org/cudnn", t);
                 }
             }
         }