diff --git a/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/exceptions/InvalidKerasConfigurationException.java b/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/exceptions/InvalidKerasConfigurationException.java
index db51cb499..dbebac7b9 100644
--- a/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/exceptions/InvalidKerasConfigurationException.java
+++ b/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/exceptions/InvalidKerasConfigurationException.java
@@ -21,7 +21,7 @@ package org.deeplearning4j.nn.modelimport.keras.exceptions;
* Indicates that user is attempting to import a Keras model configuration that
* is malformed or invalid in some other way.
*
- * See https://deeplearning4j.org/docs/latest/keras-import-overview for more information.
+ * See https://deeplearning4j.konduit.ai/keras-import/overview for more information.
*
* @author dave@skymind.io
*/
@@ -40,6 +40,6 @@ public class InvalidKerasConfigurationException extends Exception {
}
private static String appendDocumentationURL(String message) {
- return message + ". For more information, see http://deeplearning4j.org/docs/latest/keras-import-overview";
+ return message + ". For more information, see https://deeplearning4j.konduit.ai/keras-import/overview";
}
}
diff --git a/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/exceptions/UnsupportedKerasConfigurationException.java b/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/exceptions/UnsupportedKerasConfigurationException.java
index 6244cf1e8..999682a8b 100644
--- a/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/exceptions/UnsupportedKerasConfigurationException.java
+++ b/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/exceptions/UnsupportedKerasConfigurationException.java
@@ -21,7 +21,7 @@ package org.deeplearning4j.nn.modelimport.keras.exceptions;
* Indicates that user is attempting to import a Keras model configuration that
* is not currently supported.
*
- * See https://deeplearning4j.org/docs/latest/keras-import-overview
+ * See https://deeplearning4j.konduit.ai/keras-import/overview
* for more information and file an issue at https://github.com/eclipse/deeplearning4j/issues.
*
* @author dave@skymind.io
diff --git a/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/embeddings/KerasEmbedding.java b/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/embeddings/KerasEmbedding.java
index f5a29d4f5..03f7ada88 100644
--- a/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/embeddings/KerasEmbedding.java
+++ b/deeplearning4j/deeplearning4j-modelimport/src/main/java/org/deeplearning4j/nn/modelimport/keras/layers/embeddings/KerasEmbedding.java
@@ -103,7 +103,7 @@ public class KerasEmbedding extends KerasLayer {
"on Embedding layers. Zero Masking for the Embedding layer only works with unidirectional LSTM for now."
+ " If you want to have this behaviour for your imported model " +
"in DL4J, apply masking as a pre-processing step to your input." +
- "See http://deeplearning4j.org/docs/latest/deeplearning4j-nn-recurrent#masking for more on this.");
+ "See https://deeplearning4j.konduit.ai/models/recurrent#masking-one-to-many-many-to-one-and-sequence-classification for more on this.");
IWeightInit init = getWeightInitFromConfig(layerConfig, conf.getLAYER_FIELD_EMBEDDING_INIT(),
enforceTrainingConfig, conf, kerasMajorVersion);
diff --git a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/WorkspaceMode.java b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/WorkspaceMode.java
index 8824ad2ca..2a754d07d 100644
--- a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/WorkspaceMode.java
+++ b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/WorkspaceMode.java
@@ -17,10 +17,10 @@
package org.deeplearning4j.nn.conf;
/**
- * Workspace mode to use. See https://deeplearning4j.org/docs/latest/deeplearning4j-config-workspaces
+ * Workspace mode to use. See https://deeplearning4j.konduit.ai/config/config-memory/config-workspaces
*
* NONE: No workspaces will be used for the network. Highest memory use, least performance.
- * ENABLED: Use workspaces.
+ * ENABLED: Use workspaces. This is the default and should almost always be used
* SINGLE: Deprecated. Now equivalent to ENABLED, which should be used instead.
* SEPARATE: Deprecated. Now equivalent to ENABLED, which sohuld be used instead.
*
diff --git a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/layers/LSTM.java b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/layers/LSTM.java
index 684f0df71..ba0b52d8c 100644
--- a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/layers/LSTM.java
+++ b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/conf/layers/LSTM.java
@@ -38,7 +38,7 @@ import java.util.Map;
/**
* LSTM recurrent neural network layer without peephole connections. Supports CuDNN acceleration - see https://deeplearning4j.org/docs/latest/deeplearning4j-config-cudnn for details
+ * href="https://deeplearning4j.konduit.ai/config/backends/config-cudnn">https://deeplearning4j.konduit.ai/config/backends/config-cudnn for details
*
* @author Alex Black
* @see GravesLSTM GravesLSTM class for an alternative LSTM (with peephole connections)
diff --git a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/graph/ComputationGraph.java b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/graph/ComputationGraph.java
index c648efe7b..571afea7b 100755
--- a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/graph/ComputationGraph.java
+++ b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/graph/ComputationGraph.java
@@ -1540,8 +1540,8 @@ public class ComputationGraph implements Serializable, Model, NeuralNetwork {
* (not) clearing the layer input arrays.
* Note: this method should NOT be used with clearInputs = true, unless you know what you are doing. Specifically:
* when using clearInputs=false, in combination with workspaces, the layer input fields may leak outside of the
- * workspaces in which they were defined - potentially causing a crash. See
- * https://deeplearning4j.org/docs/latest/deeplearning4j-config-workspaces
+ * workspaces in which they were defined - potentially causing a crash. See
+ * https://deeplearning4j.konduit.ai/config/config-memory/config-workspaces
* for more details
*
* @param input An array of ComputationGraph inputs
diff --git a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/layers/convolution/ConvolutionLayer.java b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/layers/convolution/ConvolutionLayer.java
index 81804a31f..d6a3bc58e 100644
--- a/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/layers/convolution/ConvolutionLayer.java
+++ b/deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/nn/layers/convolution/ConvolutionLayer.java
@@ -86,7 +86,7 @@ public class ConvolutionLayer extends BaseLayerhttps://deeplearning4j.org/docs/latest/deeplearning4j-nn-recurrent
- * READ THIS FIRST if you want to understand what the heck is happening here.
+ * RNN tutorial: https://deeplearning4j.konduit.ai/models/recurrent
+ * READ THIS FIRST if you want to understand this code.
*
* Shared code for the standard "forwards" LSTM RNN and the bidirectional LSTM RNN
* This was extracted from GravesLSTM and refactored into static helper functions. The general reasoning for this was
diff --git a/deeplearning4j/deeplearning4j-scaleout/deeplearning4j-scaleout-parallelwrapper/src/main/java/org/deeplearning4j/parallelism/ParallelWrapper.java b/deeplearning4j/deeplearning4j-scaleout/deeplearning4j-scaleout-parallelwrapper/src/main/java/org/deeplearning4j/parallelism/ParallelWrapper.java
index 8d303d391..00ca839f7 100644
--- a/deeplearning4j/deeplearning4j-scaleout/deeplearning4j-scaleout-parallelwrapper/src/main/java/org/deeplearning4j/parallelism/ParallelWrapper.java
+++ b/deeplearning4j/deeplearning4j-scaleout/deeplearning4j-scaleout-parallelwrapper/src/main/java/org/deeplearning4j/parallelism/ParallelWrapper.java
@@ -826,7 +826,7 @@ public class ParallelWrapper implements AutoCloseable {
/**
* This method allows you to specify training mode for this instance of PW.
* 1) AVERAGING - stands for parameters averaging. Each X epochs weights and updaters state will be averaged across all models
- * 2) SHARED_GRADIENTS - stands for gradients sharing - more details available here: https://deeplearning4j.org/docs/latest/deeplearning4j-scaleout-intro
+ * 2) SHARED_GRADIENTS - stands for gradients sharing - more details available here: https://deeplearning4j.konduit.ai/distributed-deep-learning/intro
* 3) CUSTOM - this method allows you to specify custom gradients accumulator, this giving you better control of configuration params for training.
*
* @param mode
diff --git a/deeplearning4j/deeplearning4j-scaleout/spark/dl4j-spark/src/main/java/org/deeplearning4j/spark/util/SparkUtils.java b/deeplearning4j/deeplearning4j-scaleout/spark/dl4j-spark/src/main/java/org/deeplearning4j/spark/util/SparkUtils.java
index d28f0fa59..0bfad5a8a 100644
--- a/deeplearning4j/deeplearning4j-scaleout/spark/dl4j-spark/src/main/java/org/deeplearning4j/spark/util/SparkUtils.java
+++ b/deeplearning4j/deeplearning4j-scaleout/spark/dl4j-spark/src/main/java/org/deeplearning4j/spark/util/SparkUtils.java
@@ -71,7 +71,7 @@ public class SparkUtils {
+ "for ND4J INDArrays.\nWhen using Kryo, An appropriate Kryo registrator must be used to avoid"
+ " serialization issues (NullPointerException) with off-heap data in INDArrays.\n"
+ "Use nd4j-kryo_2.10 or _2.11 artifact, with sparkConf.set(\"spark.kryo.registrator\", \"org.nd4j.kryo.Nd4jRegistrator\");\n"
- + "See https://deeplearning4j.org/docs/latest/deeplearning4j-scaleout-howto#kryo for more details";
+ + "See https://deeplearning4j.konduit.ai/distributed-deep-learning/howto#how-to-use-kryo-serialization-with-dl-4-j-and-nd-4-j for more details";
private static String sparkExecutorId;
diff --git a/deeplearning4j/deeplearning4j-scaleout/spark/dl4j-spark/src/test/java/org/deeplearning4j/spark/impl/multilayer/TestSparkDl4jMultiLayer.java b/deeplearning4j/deeplearning4j-scaleout/spark/dl4j-spark/src/test/java/org/deeplearning4j/spark/impl/multilayer/TestSparkDl4jMultiLayer.java
index 38a15ef8d..4903091c6 100644
--- a/deeplearning4j/deeplearning4j-scaleout/spark/dl4j-spark/src/test/java/org/deeplearning4j/spark/impl/multilayer/TestSparkDl4jMultiLayer.java
+++ b/deeplearning4j/deeplearning4j-scaleout/spark/dl4j-spark/src/test/java/org/deeplearning4j/spark/impl/multilayer/TestSparkDl4jMultiLayer.java
@@ -108,7 +108,7 @@ public class TestSparkDl4jMultiLayer extends BaseSparkTest {
.activation(Activation.SOFTMAX).nIn(100).nOut(10).build())
.build();
- //Configuration for Spark training: see https://deeplearning4j.org/docs/latest/deeplearning4j-scaleout-howto for explanation of these configuration options
+ //Configuration for Spark training: see https://deeplearning4j.konduit.ai/distributed-deep-learning/howto for explanation of these configuration options
TrainingMaster tm = new ParameterAveragingTrainingMaster.Builder(batchSizePerWorker)
.averagingFrequency(2)
diff --git a/deeplearning4j/dl4j-integration-tests/src/test/java/org/deeplearning4j/integration/testcases/dl4j/misc/CharacterIterator.java b/deeplearning4j/dl4j-integration-tests/src/test/java/org/deeplearning4j/integration/testcases/dl4j/misc/CharacterIterator.java
index 1020f1706..110bfb731 100644
--- a/deeplearning4j/dl4j-integration-tests/src/test/java/org/deeplearning4j/integration/testcases/dl4j/misc/CharacterIterator.java
+++ b/deeplearning4j/dl4j-integration-tests/src/test/java/org/deeplearning4j/integration/testcases/dl4j/misc/CharacterIterator.java
@@ -195,7 +195,7 @@ public class CharacterIterator implements DataSetIterator {
// dimension 0 = number of examples in minibatch
// dimension 1 = size of each vector (i.e., number of characters)
// dimension 2 = length of each time series/example
- //Why 'f' order here? See https://deeplearning4j.org/docs/latest/deeplearning4j-nn-recurrent data section "Alternative: Implementing a custom DataSetIterator"
+ //Why 'f' order here? See https://deeplearning4j.konduit.ai/models/recurrent data section "Alternative: Implementing a custom DataSetIterator"
INDArray input = Nd4j.create(new int[]{currMinibatchSize, validCharacters.length, exampleLength}, 'f');
INDArray labels = Nd4j.create(new int[]{currMinibatchSize, validCharacters.length, exampleLength}, 'f');
diff --git a/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/executioner/DefaultOpExecutioner.java b/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/executioner/DefaultOpExecutioner.java
index 9f4217b68..af3ffb2c4 100644
--- a/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/executioner/DefaultOpExecutioner.java
+++ b/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/executioner/DefaultOpExecutioner.java
@@ -61,7 +61,7 @@ import java.util.*;
@Slf4j
public abstract class DefaultOpExecutioner implements OpExecutioner {
- private static final String SCOPE_PANIC_MSG = "For more details, see the ND4J User Guide: deeplearning4j.org/docs/latest/nd4j-overview#workspaces-panic";
+ private static final String SCOPE_PANIC_MSG = "For more details, see the ND4J User Guide: https://deeplearning4j.konduit.ai/nd4j/overview#workspaces-scope-panic";
protected ProfilingMode profilingMode = ProfilingMode.SCOPE_PANIC;