Nd4j: Change array args to vararg and add toString options (#36)

* changed [] to ...

Signed-off-by: Ryan Nett <rnett@skymind.io>

* added randn(long seed, int... shape)

Signed-off-by: Ryan Nett <rnett@skymind.io>

* Fixed a couple of methods

Signed-off-by: Ryan Nett <rnett@skymind.io>

* ToString methods w/ options

Signed-off-by: Ryan Nett <rnett@skymind.io>

* fixes, less toString methods, and a few ops I missed

Signed-off-by: Ryan Nett <rnett@skymind.io>

* some javadocs, change int... to long... where possible

Signed-off-by: Ryan Nett <rnett@skymind.io>

* another javadoc

Signed-off-by: Ryan Nett <rnett@skymind.io>

* javadoc fix

Signed-off-by: Ryan Nett <rnett@skymind.io>

* just javadoc in INDArray

Signed-off-by: Ryan Nett <rnett@skymind.io>

* local/static fix

Signed-off-by: Ryan Nett <rnett@skymind.io>

* Add @NonNull to options

Signed-off-by: Ryan Nett <rnett@skymind.io>

* javadoc updates/fixes

Signed-off-by: Ryan Nett <rnett@skymind.io>

* more @NonNulls

Signed-off-by: Ryan Nett <rnett@skymind.io>

* even more @NonNulls, this time on varargs

Signed-off-by: Ryan Nett <rnett@skymind.io>

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseNDArray.java

@@ -38,7 +38,6 @@ import org.nd4j.linalg.api.iter.NdIndexIterator;
 import org.nd4j.linalg.api.memory.MemoryWorkspace;
 import org.nd4j.linalg.api.ops.CustomOp;
 import org.nd4j.linalg.api.ops.DynamicCustomOp;
-import org.nd4j.linalg.api.ops.custom.BarnesHutGains;
 import org.nd4j.linalg.api.ops.impl.reduce.bool.All;
 import org.nd4j.linalg.api.ops.impl.reduce.bool.Any;
 import org.nd4j.linalg.api.ops.impl.reduce.floating.*;
@@ -5995,13 +5994,30 @@ public abstract class BaseNDArray implements INDArray, Iterable {
      */
     @Override
     public String toString() {
+        return toString(new NDArrayStrings());
+    }
+
+
+    @Override
+    public String toString(@NonNull NDArrayStrings options){
         if (!isCompressed() && !preventUnpack)
-            return new NDArrayStrings().format(this);
+            return options.format(this);
         else if (isCompressed() && compressDebug)
             return "COMPRESSED ARRAY. SYSTEM PROPERTY compressdebug is true. This is to prevent auto decompression from being triggered.";
         else if (preventUnpack)
             return "Array string unpacking is disabled.";
-        return new NDArrayStrings().format(this);
+        return options.format(this);
+    }
+
+    @Override
+    public String toString(long maxElements, boolean forceSummarize, int precision){
+        return toString(new NDArrayStrings(maxElements, forceSummarize, precision));
+    }
+
+
+    @Override
+    public String toStringFull(){
+        return toString(Long.MAX_VALUE, false, -1 * dataType().precision());
     }
 
     /**

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseSparseNDArray.java

@@ -39,6 +39,7 @@ import org.nd4j.linalg.indexing.INDArrayIndex;
 import org.nd4j.linalg.indexing.SpecifiedIndex;
 import org.nd4j.linalg.indexing.conditions.Condition;
 import org.nd4j.linalg.primitives.Pair;
+import org.nd4j.linalg.string.NDArrayStrings;
 import org.nd4j.linalg.util.LinAlgExceptions;
 
 import java.nio.LongBuffer;
@@ -47,7 +48,9 @@ import java.util.Arrays;
 import java.util.List;
 import java.util.NoSuchElementException;
 
+import static org.nd4j.linalg.factory.Nd4j.compressDebug;
 import static org.nd4j.linalg.factory.Nd4j.createUninitialized;
+import static org.nd4j.linalg.factory.Nd4j.preventUnpack;
 
 /**
  * @author Audrey Loeffel
@@ -2016,4 +2019,24 @@ public abstract class BaseSparseNDArray implements ISparseNDArray {
     public INDArray ulike() {
         throw new UnsupportedOperationException("Not yet implemented");
     }
+
+    @Override
+    public String toString(NDArrayStrings options){
+        return "SPARSE ARRAY, TOSTRING NOT SUPPORTED";
+    }
+
+    @Override
+    public String toString(long maxElements, boolean forceSummarize, int decimalPlaces){
+        return toString(new NDArrayStrings(maxElements, forceSummarize, decimalPlaces));
+    }
+
+    @Override
+    public String toStringFull(){
+        return toString(Long.MAX_VALUE, false, dataType().precision());
+    }
+
+    @Override
+    public String toString(){
+        return toString(new NDArrayStrings());
+    }
 }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/INDArray.java

@@ -16,7 +16,11 @@
 
 package org.nd4j.linalg.api.ndarray;
 
+import static org.nd4j.linalg.factory.Nd4j.compressDebug;
+import static org.nd4j.linalg.factory.Nd4j.preventUnpack;
+
 import com.google.flatbuffers.FlatBufferBuilder;
+import lombok.NonNull;
 import org.nd4j.linalg.api.blas.params.MMulTranspose;
 import org.nd4j.linalg.api.buffer.DataBuffer;
 import org.nd4j.linalg.api.buffer.DataType;
@@ -28,6 +32,7 @@ import org.nd4j.linalg.indexing.conditions.Condition;
 import java.io.Serializable;
 import java.nio.LongBuffer;
 import java.util.List;
+import org.nd4j.linalg.string.NDArrayStrings;
 
 /**
  * Interface for an ndarray
@@ -1914,7 +1919,7 @@ public interface INDArray extends Serializable, AutoCloseable {
      * @param shape
      * @param stride
      */
-    public void setShapeAndStride(int[] shape, int[] stride);
+    void setShapeAndStride(int[] shape, int[] stride);
 
     /**
      * Set the ordering
@@ -2843,4 +2848,26 @@ public interface INDArray extends Serializable, AutoCloseable {
      * @return
      */
     //INDArray[] gains(INDArray input, INDArray gradx, INDArray epsilon);
+
+    /**
+     * Get a string representation of the array with configurable formatting
+     * @param options format options
+     */
+    String toString(@NonNull NDArrayStrings options);
+
+
+    /**
+     * Get a string representation of the array
+     *
+     * @param maxElements Summarize if more than maxElements in the array
+     * @param forceSummarize Force a summary instead of a full print
+     * @param precision The number of decimals to print.  Doesn't print trailing 0s if negative
+     */
+    String toString(long maxElements, boolean forceSummarize, int precision);
+
+    /**
+     * ToString with unlimited elements and precision
+     * @see org.nd4j.linalg.api.ndarray.BaseNDArray#toString(long, boolean, int)
+     */
+    String toStringFull();
 }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/factory/Nd4j.java

@@ -407,7 +407,7 @@ public class Nd4j {
      * @param dimension the dimension to do the shuffle
      * @return
      */
-    public static void shuffle(INDArray toShuffle, Random random, int... dimension) {
+    public static void shuffle(INDArray toShuffle, Random random, @NonNull int... dimension) {
         INSTANCE.shuffle(toShuffle, random, dimension);
     }
 
@@ -418,7 +418,7 @@ public class Nd4j {
      * @param dimension the dimension to do the shuffle
      * @return
      */
-    public static void shuffle(INDArray toShuffle, int... dimension) {
+    public static void shuffle(INDArray toShuffle, @NonNull int... dimension) {
         //shuffle(toShuffle, new Random(), dimension);
         INSTANCE.shuffle(toShuffle, new Random(), dimension);
     }
@@ -430,7 +430,7 @@ public class Nd4j {
      * @param dimension the dimension to do the shuffle
      * @return
      */
-    public static void shuffle(Collection<INDArray> toShuffle, int... dimension) {
+    public static void shuffle(Collection<INDArray> toShuffle, @NonNull int... dimension) {
         //shuffle(toShuffle, new Random(), dimension);
         INSTANCE.shuffle(toShuffle, new Random(), dimension);
     }
@@ -442,7 +442,7 @@ public class Nd4j {
      * @param dimension the dimension to do the shuffle
      * @return
      */
-    public static void shuffle(Collection<INDArray> toShuffle, Random rnd, int... dimension) {
+    public static void shuffle(Collection<INDArray> toShuffle, Random rnd, @NonNull int... dimension) {
         //shuffle(toShuffle, new Random(), dimension);
         INSTANCE.shuffle(toShuffle, rnd, dimension);
     }
@@ -659,7 +659,7 @@ public class Nd4j {
      * @param dimension the dimension along which to get the maximum
      * @return array of maximum values.
      */
-    public static INDArray argMax(INDArray arr, int... dimension) {
+    public static INDArray argMax(INDArray arr, @NonNull int... dimension) {
         IMax imax = new IMax(arr, dimension);
         return Nd4j.getExecutioner().exec(imax);
     }
@@ -667,7 +667,7 @@ public class Nd4j {
     /**
      * @see #argMax(INDArray, int...)
      */
-    public static INDArray argMin(INDArray arr, int... dimension) {
+    public static INDArray argMin(INDArray arr, @NonNull int... dimension) {
         IMin imin = new IMin(arr, dimension);
         return Nd4j.getExecutioner().exec(imin);
     }
@@ -2325,7 +2325,7 @@ public class Nd4j {
      * @return the flattened representation of
      * these ndarrays
      */
-    public static INDArray toFlattened(INDArray... matrices) {
+    public static INDArray toFlattened(@NonNull INDArray... matrices) {
         return INSTANCE.toFlattened(matrices);
     }
 
@@ -2337,7 +2337,7 @@ public class Nd4j {
      * @return the flattened representation of
      * these ndarrays
      */
-    public static INDArray toFlattened(char order, INDArray... matrices) {
+    public static INDArray toFlattened(char order, @NonNull INDArray... matrices) {
         return INSTANCE.toFlattened(order, matrices);
     }
 
@@ -3071,7 +3071,7 @@ public class Nd4j {
         return choice(source, probs, numSamples, Nd4j.getRandom());
     }
 
-    public static INDArray appendBias(INDArray... vectors) {
+    public static INDArray appendBias(@NonNull INDArray... vectors) {
         INDArray ret = INSTANCE.appendBias(vectors);
         return ret;
     }
@@ -3092,13 +3092,12 @@ public class Nd4j {
     ////////////////////// RANDOM ///////////////////////////////
 
     /**
-     * Create a random ndarray with the given shape using
-     * the current time as the seed
+     * Create a random ndarray with values from a uniform distribution over (0, 1) with the given shape
      *
      * @param shape the shape of the array
      * @return the random ndarray with the specified shape
      */
-    public static INDArray rand(int[] shape) {
+    public static INDArray rand(@NonNull int... shape) {
         INDArray ret = createUninitialized(shape, order()); //INSTANCE.rand(shape, Nd4j.getRandom());
         return rand(ret);
     }
@@ -3106,18 +3105,20 @@ public class Nd4j {
     /**
      * @see #rand(int[])
      */
-    public static INDArray rand(long[] shape) {
+    public static INDArray rand(@NonNull long... shape) {
         INDArray ret = createUninitialized(shape, order()); //INSTANCE.rand(shape, Nd4j.getRandom());
         return rand(ret);
     }
 
     /**
-     * Create a random ndarray with given type and shape.
-     * @param dataType datatype
-     * @param shape shape
-     * @return new array.
+     * Create a random ndarray with values from a uniform distribution over (0, 1) with the given shape and data type
+     *
+     * @param shape the shape of the ndarray
+     * @return the random ndarray with the specified shape
      */
-    public static INDArray rand(DataType dataType, long... shape) {
+    public static INDArray rand(@NonNull DataType dataType, @NonNull long... shape) {
+        Preconditions.checkArgument(dataType.isFPType(),
+                "Can't create a random array of a non-floating point data type");
         INDArray ret = createUninitialized(dataType, shape, order()); //INSTANCE.rand(shape, Nd4j.getRandom());
         return rand(ret);
     }
@@ -3125,52 +3126,65 @@ public class Nd4j {
     /**
      * Create a random ndarray with the given shape and array order
      *
+     * Values are sampled from a uniform distribution over (0, 1)
+     *
      * @param order the order of the ndarray to return
      * @param shape the shape of the array
      * @return the random ndarray with the specified shape
      */
-    public static INDArray rand(char order, int[] shape) {
+    public static INDArray rand(char order, @NonNull int... shape) {
         INDArray ret = Nd4j.createUninitialized(shape, order); //INSTANCE.rand(order, shape);
         return rand(ret);
     }
 
     /**
-     * Create a random ndarray with the given datatype, order and shape.
-     *
-     * The datatype must be one of the floating point types.
-     *
-     * @param dataType datatype
-     * @param order order
-     * @param shape shape
-     * @return
+     * @deprecated use {@link Nd4j#rand(org.nd4j.linalg.api.buffer.DataType, char, long...))
      */
-    public static INDArray rand(DataType dataType, char order, int[] shape) {
-        INDArray ret = Nd4j.createUninitialized(dataType, ArrayUtil.toLongArray(shape), order); //INSTANCE.rand(order, shape);
-        return rand(ret);
+    @Deprecated
+    public static INDArray rand(@NonNull DataType dataType, int[] shape, char order) {
+        return rand(dataType, order, ArrayUtil.toLongArray(shape));
     }
 
     /**
-     * @see #rand(DataType, char, int[])
+     * @deprecated use {@link org.nd4j.linalg.factory.Nd4j#rand(org.nd4j.linalg.api.buffer.DataType, char, long...)}
      */
-    public static INDArray rand(DataType dataType, int[] shape, char order) {
-        INDArray ret = Nd4j.createUninitialized(dataType, ArrayUtil.toLongArray(shape), order); //INSTANCE.rand(order, shape);
-        return rand(ret);
+    @Deprecated
+    public static INDArray rand(@NonNull DataType dataType, char order, @NonNull int... shape) {
+        return rand(dataType, order, ArrayUtil.toLongArray(shape));
     }
 
     /**
-     * Create a random ndarray with the given datatype and shape.
-     * using the default Nd4j order.
+     * Create a random ndarray with the given shape, data type, and array order
      *
-     * @see #rand(DataType, char, int[])
+     * Values are sampled from a uniform distribution over (0, 1)
+     *
+     * @param order the order of the ndarray to return
+     * @param shape the shape of the ndarray
+     * @param dataType the data type of the ndarray
+     * @return the random ndarray with the specified shape
      */
-    public static INDArray rand(DataType dataType, int[] shape) {
+    public static INDArray rand(@NonNull DataType dataType, char order, @NonNull long... shape) {
+        INDArray ret = Nd4j.createUninitialized(dataType, shape, order); //INSTANCE.rand(order, shape);
+        return rand(ret);
+    }
+
+
+    /**
+     * Create a random ndarray with the given shape and data type
+     *
+     * Values are sampled from a uniform distribution over (0, 1)
+     *
+     * @param shape the shape of the ndarray
+     * @param dataType the data type of the ndarray
+     * @return the random ndarray with the specified shape
+     */
+    public static INDArray rand(@NonNull DataType dataType, @NonNull int... shape) {
         INDArray ret = Nd4j.createUninitialized(dataType, ArrayUtil.toLongArray(shape), Nd4j.order()); //INSTANCE.rand(order, shape);
         return rand(ret);
     }
 
     /**
-     * Create a random ndarray with the given shape using
-     * the current time as the seed
+     * Create a random ndarray with values from a uniform distribution over (0, 1) with the given shape
      *
      * @param rows    the number of rows in the matrix
      * @param columns the number of columns in the matrix
@@ -3187,6 +3201,8 @@ public class Nd4j {
     /**
      * Create a random ndarray with the given shape and output order
      *
+     * Values are sampled from a uniform distribution over (0, 1)
+     *
      * @param rows    the number of rows in the matrix
      * @param columns the number of columns in the matrix
      * @return the random ndarray with the specified shape
@@ -3200,20 +3216,31 @@ public class Nd4j {
     }
 
     /**
-     * Create a random ndarray with the given shape using given seed
+     * Create a random ndarray with values from a uniform distribution over (0, 1) with the given shape
+     * using given seed
      *
      * @param shape the shape of the array
      * @param seed  the  seed to use
      * @return the random ndarray with the specified shape
      */
-    public static INDArray rand(int[] shape, long seed) {
+    public static INDArray rand(long seed, @NonNull long... shape) {
         INDArray ret = createUninitialized(shape, Nd4j.order());//;INSTANCE.rand(shape, seed);
         return rand(ret, seed);
     }
 
+    /**
+     * @deprecated use {@link Nd4j#rand(long, long...)}
+     */
+    @Deprecated
+    public static INDArray rand(int[] shape, long seed) {
+        INDArray ret = createUninitialized(shape, Nd4j.order());//;INSTANCE.rand(shape, seed);
+        return rand(seed, ArrayUtil.toLongArray(shape));
+    }
+
 
     /**
-     * Create a random ndarray with the given shape using the given seed
+     * Create a random ndarray with values from a uniform distribution over (0, 1) with the given shape
+     * using the given seed
      *
      * @param rows    the number of rows in the matrix
      * @param columns the columns of the ndarray
@@ -3225,6 +3252,14 @@ public class Nd4j {
         return rand(ret, seed);
     }
 
+    /**
+     * @deprecated use {@link Nd4j#rand(org.nd4j.linalg.api.rng.Random, long...)}
+     */
+    @Deprecated
+    public static INDArray rand(int[] shape, @NonNull org.nd4j.linalg.api.rng.Random rng) {
+        return rand(rng, ArrayUtil.toLongArray(shape));
+    }
+
     /**
      * Create a random ndarray with the given shape using the given RandomGenerator
      *
@@ -3232,22 +3267,26 @@ public class Nd4j {
      * @param rng     the random generator to use
      * @return the random ndarray with the specified shape
      */
-    public static INDArray rand(int[] shape, org.nd4j.linalg.api.rng.Random rng) {
+    public static INDArray rand(@NonNull org.nd4j.linalg.api.rng.Random rng, @NonNull long... shape) {
         INDArray ret = createUninitialized(shape, Nd4j.order()); //INSTANCE.rand(shape, rng);
         return rand(ret, rng);
     }
 
     /**
-     * Create a random ndarray with the given shape using the given rng
-     *
-     * @param shape the shape of the array
-     * @param dist  distribution to use
-     * @return the random ndarray with the specified shape
+     * @deprecated use {@link Nd4j#rand(org.nd4j.linalg.api.rng.distribution.Distribution, long...)}
      */
-    public static INDArray rand(int[] shape, Distribution dist) {
-        //INDArray ret = INSTANCE.rand(shape, dist);
-        //logCreationIfNecessary(ret);
-        return dist.sample(shape);
+    @Deprecated
+    public static INDArray rand(int[] shape, @NonNull Distribution dist) {
+        return rand(dist, ArrayUtil.toLongArray(shape));
+    }
+
+    /**
+     * @deprecated use
+     * {@link org.nd4j.linalg.factory.Nd4j#rand(org.nd4j.linalg.api.rng.distribution.Distribution, long...)}
+     */
+    @Deprecated
+    public static INDArray rand(long[] shape, @NonNull Distribution dist) {
+        return rand(dist, shape);
     }
 
     /**
@@ -3257,7 +3296,7 @@ public class Nd4j {
      * @param dist  distribution to use
      * @return the random ndarray with the specified shape
      */
-    public static INDArray rand(long[] shape, Distribution dist) {
+    public static INDArray rand(@NonNull Distribution dist, @NonNull long... shape) {
         //INDArray ret = INSTANCE.rand(shape, dist);
         //logCreationIfNecessary(ret);
         return dist.sample(shape);
@@ -3271,21 +3310,24 @@ public class Nd4j {
      * @param rng       the random generator to use
      * @return the random ndarray with the specified shape
      */
-    public static INDArray rand(int rows, int columns, org.nd4j.linalg.api.rng.Random rng) {
+    public static INDArray rand(int rows, int columns, @NonNull org.nd4j.linalg.api.rng.Random rng) {
         INDArray ret = createUninitialized(new int[] {rows, columns}, order());//INSTANCE.rand(rows, columns, rng);
         return rand(ret, rng);
     }
 
     /**
-     * Generates a random matrix between min and max
-     *
-     * @param shape the number of rows of the matrix
-     * @param min   the minimum number
-     * @param max   the maximum number
-     * @param rng   the rng to use
-     * @return a random matrix of the specified shape and range
+     * @deprecated use {@link Nd4j#rand(double, double, org.nd4j.linalg.api.rng.Random, long...)}
      */
-    public static INDArray rand(int[] shape, double min, double max, org.nd4j.linalg.api.rng.Random rng) {
+    @Deprecated
+    public static INDArray rand(int[] shape, double min, double max, @NonNull org.nd4j.linalg.api.rng.Random rng) {
+        return rand(min, max, rng, ArrayUtil.toLongArray(shape));
+    }
+
+    /**
+     * @deprecated use {@link Nd4j#rand(double, double, org.nd4j.linalg.api.rng.Random, long...)}
+     */
+    @Deprecated
+    public static INDArray rand(long[] shape, double min, double max, @NonNull org.nd4j.linalg.api.rng.Random rng) {
         INDArray ret = createUninitialized(shape, order()); //INSTANCE.rand(shape, min, max, rng);
         return rand(ret, min, max, rng);
     }
@@ -3299,7 +3341,7 @@ public class Nd4j {
      * @param rng   the rng to use
      * @return a random matrix of the specified shape and range
      */
-    public static INDArray rand(long[] shape, double min, double max, org.nd4j.linalg.api.rng.Random rng) {
+    public static INDArray rand(double min, double max, @NonNull org.nd4j.linalg.api.rng.Random rng, @NonNull long... shape) {
         INDArray ret = createUninitialized(shape, order()); //INSTANCE.rand(shape, min, max, rng);
         return rand(ret, min, max, rng);
     }
@@ -3314,7 +3356,7 @@ public class Nd4j {
      * @param rng     the rng to use
      * @return a drandom matrix of the specified shape and range
      */
-    public static INDArray rand(int rows, int columns, double min, double max, org.nd4j.linalg.api.rng.Random rng) {
+    public static INDArray rand(int rows, int columns, double min, double max, @NonNull org.nd4j.linalg.api.rng.Random rng) {
         INDArray ret = createUninitialized(rows, columns);//INSTANCE.rand(rows, columns, min, max, rng);
         return rand(ret, min, max, rng);
     }
@@ -3330,34 +3372,47 @@ public class Nd4j {
     }
 
     /**
-     * Random normal using the current time stamp
-     * as the seed
+     * Create a ndarray of the given shape with values from N(0,1)
      *
      * @param shape the shape of the array
      * @return new array with random values
      */
-    public static INDArray randn(int[] shape) {
-        INDArray ret = Nd4j.createUninitialized(shape, order());
-        return randn(ret);
+    public static INDArray randn(@NonNull int... shape) {
+        return randn(ArrayUtil.toLongArray(shape));
+    }
+
+
+    /**
+     * Create a ndarray of the given shape and data type with values from N(0,1)
+     *
+     * @param shape the shape of the ndarray
+     * @return
+     */
+    public static INDArray randn(@NonNull DataType dataType, @NonNull int... shape) {
+        return randn(dataType, ArrayUtil.toLongArray(shape));
     }
 
     /**
-     * Random normal ndarray of given datatype and shape,
+     * Create a ndarray of the given shape and data type with values from N(0,1)
+     *
      * @param dataType datatype to use, must be a float type datatype.
      * @param shape shape for the new array.
      * @return new array with random values
      */
-    public static INDArray randn(DataType dataType, long... shape) {
+    public static INDArray randn(@NonNull DataType dataType, @NonNull long... shape) {
         INDArray ret = Nd4j.createUninitialized(dataType, shape, order());
         return randn(ret);
     }
 
+
     /**
-     * Random normal ndarray of given shape. defaults to FLOAT and c-order.
+     * Create a ndarray of the given shape with values from N(0,1).
+     * Defaults to FLOAT and c-order.
+     *
      * @param shape shape for the new array.
      * @return new array with random values
      */
-    public static INDArray randn(long... shape) {
+    public static INDArray randn(@NonNull long... shape) {
         INDArray ret = Nd4j.createUninitialized(shape, order());
         return randn(ret);
     }
@@ -3369,7 +3424,7 @@ public class Nd4j {
      * @param shape the shape of the array
      * @return new array with random values
      */
-    public static INDArray randn(char order, int[] shape) {
+    public static INDArray randn(char order, @NonNull int... shape) {
         INDArray ret = Nd4j.createUninitialized(shape, order);
         return randn(ret);
     }
@@ -3381,34 +3436,45 @@ public class Nd4j {
      * @param shape the shape of the array
      * @return new array with random values
      */
-    public static INDArray randn(char order, long[] shape) {
+    public static INDArray randn(char order, @NonNull long... shape) {
         INDArray ret = Nd4j.createUninitialized(shape, order);
         return randn(ret);
     }
 
 
     /**
-     * @see #rand(DataType, char, int[])
+     * Random normal N(0,1) with the specified shape and array order
+     *
+     * @param order order of the output ndarray
+     * @param shape the shape of the ndarray
+     * @param dataType the data type of the ndarray
      */
-    public static INDArray randn(DataType dataType, char order, long[] shape) {
+    public static INDArray randn(@NonNull DataType dataType, char order, @NonNull long... shape) {
         INDArray ret = Nd4j.createUninitialized(dataType, shape, order);
         return randn(ret);
     }
 
     /**
-     * Random normal using the specified seed
+     * @deprecated use {@link Nd4j#randn(long, long...)}
+     */
+    @Deprecated
+    public static INDArray randn(int[] shape, long seed) {
+        return randn(seed, ArrayUtil.toLongArray(shape));
+    }
+
+    /**
+     * Random normal N(0, 1) using the specified seed
      *
      * @param shape the shape of the array
      * @return
      */
-    public static INDArray randn(int[] shape, long seed) {
+    public static INDArray randn(long seed, @NonNull long... shape) {
         INDArray ret = Nd4j.createUninitialized(shape, order());
         return randn(ret, seed);
     }
 
     /**
-     * Random normal using the current time stamp
-     * as the seed
+     * Random normal N(0, 1)
      *
      * @param rows    the number of rows in the matrix
      * @param columns the number of columns in the matrix
@@ -3451,21 +3517,25 @@ public class Nd4j {
      * @param r       the random generator to use
      * @return
      */
-    public static INDArray randn(long rows, long columns, org.nd4j.linalg.api.rng.Random r) {
+    public static INDArray randn(long rows, long columns, @NonNull org.nd4j.linalg.api.rng.Random r) {
         INDArray ret = Nd4j.createUninitialized(new long[]{rows, columns}, order());
         return randn(ret, r);
     }
 
     /**
-     * Random normal using the given rng
-     *
-     * @param shape the shape of the array
-     * @param r     the random generator to use
-     * @return
+     * @deprecated use {@link Nd4j#randn(org.nd4j.linalg.api.rng.Random, long...)}
      */
-    public static INDArray randn(int[] shape, org.nd4j.linalg.api.rng.Random r) {
-        final INDArray ret = Nd4j.createUninitialized(shape, order());
-        return randn(ret, r);
+    @Deprecated
+    public static INDArray randn(int[] shape, @NonNull org.nd4j.linalg.api.rng.Random r) {
+        return randn(r, ArrayUtil.toLongArray(shape));
+    }
+
+    /**
+     * @deprecated use {@link Nd4j#randn(org.nd4j.linalg.api.rng.Random, long...)}
+     */
+    @Deprecated
+    public static INDArray randn(long[] shape, @NonNull org.nd4j.linalg.api.rng.Random r) {
+        return randn(r, shape);
     }
 
     /**
@@ -3475,7 +3545,7 @@ public class Nd4j {
      * @param r     the random generator to use
      * @return
      */
-    public static INDArray randn(long[] shape, org.nd4j.linalg.api.rng.Random r) {
+    public static INDArray randn(@NonNull org.nd4j.linalg.api.rng.Random r, @NonNull long... shape) {
         final INDArray ret = Nd4j.createUninitialized(shape, order());
         return randn(ret, r);
     }
@@ -3509,7 +3579,7 @@ public class Nd4j {
      * @param rng     the random generator to use
      * @return the given target array
      */
-    public static INDArray rand(INDArray target, org.nd4j.linalg.api.rng.Random rng) {
+    public static INDArray rand(INDArray target, @NonNull org.nd4j.linalg.api.rng.Random rng) {
         return getExecutioner().exec(new UniformDistribution(target), rng);
     }
 
@@ -3520,7 +3590,7 @@ public class Nd4j {
      * @param dist  distribution to use
      * @return the random ndarray with the specified shape
      */
-    public static INDArray rand(INDArray target, Distribution dist) {
+    public static INDArray rand(INDArray target, @NonNull Distribution dist) {
         return dist.sample(target);
     }
 
@@ -3533,7 +3603,7 @@ public class Nd4j {
      * @param rng     the random generator to use
      * @return the given target array
      */
-    public static INDArray rand(INDArray target,  double min, double max, org.nd4j.linalg.api.rng.Random rng) {
+    public static INDArray rand(INDArray target,  double min, double max, @NonNull org.nd4j.linalg.api.rng.Random rng) {
         if (min > max)
             throw new IllegalArgumentException("the maximum value supplied is smaller than the minimum");
         return getExecutioner().exec(new UniformDistribution(target, min, max), rng);
@@ -3557,7 +3627,7 @@ public class Nd4j {
      * @param rng     the random generator to use
      * @return the given target array
      */
-    public static INDArray randn(INDArray target, org.nd4j.linalg.api.rng.Random rng) {
+    public static INDArray randn(INDArray target, @NonNull org.nd4j.linalg.api.rng.Random rng) {
         return getExecutioner().exec(new GaussianDistribution(target), rng);
     }
 
@@ -3569,7 +3639,7 @@ public class Nd4j {
      * @param shape Shape of the result array
      * @return Result array
      */
-    public static INDArray randomBernoulli(double p, long... shape) {
+    public static INDArray randomBernoulli(double p, @NonNull long... shape) {
         return randomBernoulli(p, Nd4j.createUninitialized(shape));
     }
 
@@ -3595,7 +3665,7 @@ public class Nd4j {
      * @param shape   Shape of the result array
      * @return Result array
      */
-    public static INDArray randomBinomial(int nTrials, double p, long... shape) {
+    public static INDArray randomBinomial(int nTrials, double p, @NonNull long... shape) {
         return randomBinomial(nTrials, p, Nd4j.createUninitialized(shape));
     }
 
@@ -3757,7 +3827,7 @@ public class Nd4j {
      * @param shape desired shape of new array.
      * @return the created ndarray.
      */
-    public static INDArray create(boolean[][] data, long[] shape) {
+    public static INDArray create(boolean[][] data, @NonNull long... shape) {
         return INSTANCE.create(ArrayUtil.flatten(data), shape, getStrides(shape), DataType.BOOL, Nd4j.getMemoryManager().getCurrentWorkspace());
     }
 
@@ -4083,7 +4153,7 @@ public class Nd4j {
      * @param shape the shape of the array
      * @return the created ndarray
      */
-    public static INDArray create(float[] data, int[] shape) {
+    public static INDArray create(float[] data, int... shape) {
         if (shape.length == 0 && data.length == 1) {
             return scalar(data[0]);
         }
@@ -4102,7 +4172,7 @@ public class Nd4j {
     /**
      * @see #create(float[], int[])
      */
-    public static INDArray create(float[] data, long[] shape) {
+    public static INDArray create(float[] data, long... shape) {
         if (shape.length == 0 && data.length == 1) {
             return scalar(data[0]);
         }
@@ -4121,7 +4191,7 @@ public class Nd4j {
     /**
      * @see #create(float[], int[])
      */
-    public static INDArray create(double[] data, long[] shape) {
+    public static INDArray create(double[] data, long... shape) {
         if (shape.length == 0 && data.length == 1) {
             return scalar(data[0]);
         }
@@ -4144,7 +4214,7 @@ public class Nd4j {
      * @param shape the shape of the array
      * @return the created ndarray
      */
-    public static INDArray create(double[] data, int[] shape) {
+    public static INDArray create(double[] data, int... shape) {
         if (shape.length == 1) {
             if (shape[0] != data.length)
                 throw new ND4JIllegalStateException("Shape of the new array " + Arrays.toString(shape) + " doesn't match data length: " + data.length);
@@ -4346,7 +4416,7 @@ public class Nd4j {
      * @param shape desired shape of new array. Must match the resulting shape of combining the list.
      * @return the instance
      */
-    public static INDArray create(List<INDArray> list, int[] shape) {
+    public static INDArray create(List<INDArray> list, int... shape) {
         checkShapeValues(shape);
 
         INDArray ret = INSTANCE.create(list, shape);
@@ -4356,7 +4426,7 @@ public class Nd4j {
     /**
      * @see #create(List, int[])
      */
-    public static INDArray create(List<INDArray> list, long[] shape) {
+    public static INDArray create(List<INDArray> list, long... shape) {
         checkShapeValues(shape);
 
         INDArray ret = INSTANCE.create(list, shape);
@@ -4641,7 +4711,7 @@ public class Nd4j {
      * @param shape desired shape of new array.
      * @return the created ndarray.
      */
-    public static INDArray create(DataBuffer data, int[] shape) {
+    public static INDArray create(DataBuffer data, int... shape) {
         checkShapeValues(shape);
         return INSTANCE.create(data, shape);
     }
@@ -4649,7 +4719,7 @@ public class Nd4j {
     /**
      * @see #create(DataBuffer, int[])
      */
-    public static INDArray create(DataBuffer data, long[] shape) {
+    public static INDArray create(DataBuffer data, long... shape) {
         checkShapeValues(shape);
         return INSTANCE.create(data, shape);
     }
@@ -5049,7 +5119,7 @@ public class Nd4j {
      *
      * @param shape
      */
-    public static void checkShapeValues(long[] shape) {
+    public static void checkShapeValues(long... shape) {
         for (long e: shape) {
             if (e < 0)
                 throw new ND4JIllegalStateException("Invalid shape: Requested INDArray shape " + Arrays.toString(shape)
@@ -5062,7 +5132,7 @@ public class Nd4j {
      *
      * @param shape
      */
-    public static void checkShapeValues(int[] shape) {
+    public static void checkShapeValues(int... shape) {
         for (int e: shape) {
             if (e < 1)
                 throw new ND4JIllegalStateException("Invalid shape: Requested INDArray shape " + Arrays.toString(shape)
@@ -5070,7 +5140,7 @@ public class Nd4j {
         }
     }
 
-    protected static void checkShapeValues(int length, int[] shape) {
+    protected static void checkShapeValues(int length, int... shape) {
         checkShapeValues(shape);
 
         if (ArrayUtil.prodLong(shape) > length)
@@ -5078,7 +5148,7 @@ public class Nd4j {
                     + " doesn't match data length: " + length);
     }
 
-    protected static void checkShapeValues(int length, long[] shape) {
+    protected static void checkShapeValues(int length, long... shape) {
         checkShapeValues(shape);
 
         if (ArrayUtil.prodLong(shape) > length)
@@ -5171,7 +5241,7 @@ public class Nd4j {
     /**
      * @see #createUninitialized(long[])
      */
-    public static INDArray createUninitialized(int[] shape) {
+    public static INDArray createUninitialized(int... shape) {
         if(shape.length == 0)
             return Nd4j.scalar(dataType(), 0.0);
         checkShapeValues(shape);
@@ -5186,7 +5256,7 @@ public class Nd4j {
      * @param shape the shape of the array
      * @return the instance
      */
-    public static INDArray createUninitialized(long[] shape) {
+    public static INDArray createUninitialized(long... shape) {
         checkShapeValues(shape);
         //ensure shapes that wind up being scalar end up with the write shape
         return createUninitialized(shape, Nd4j.order());
@@ -5199,7 +5269,7 @@ public class Nd4j {
      * @param shape
      * @return
      */
-    public static INDArray createUninitializedDetached(int[] shape) {
+    public static INDArray createUninitializedDetached(int... shape) {
         return createUninitializedDetached(shape, Nd4j.order());
     }
 
@@ -5210,7 +5280,7 @@ public class Nd4j {
      * @param shape
      * @return
      */
-    public static INDArray createUninitializedDetached(long[] shape) {
+    public static INDArray createUninitializedDetached(long... shape) {
         return createUninitializedDetached(shape, Nd4j.order());
     }
 
@@ -5448,7 +5518,7 @@ public class Nd4j {
      * @param shape the shape of the array
      * @return the created array.
      */
-    public static INDArray zeros(DataType dataType, long... shape) {
+    public static INDArray zeros(DataType dataType, @NonNull long... shape) {
         return INSTANCE.create(dataType, shape, 'c', Nd4j.getMemoryManager().getCurrentWorkspace());
     }
 
@@ -5621,7 +5691,7 @@ public class Nd4j {
      * @param shape Shape fo the array
      * @return the created ndarray
      */
-    public static INDArray ones(DataType dataType, long... shape) {
+    public static INDArray ones(DataType dataType, @NonNull long... shape) {
         if(shape.length == 0)
             return Nd4j.scalar(dataType, 1.0);
         INDArray ret = INSTANCE.createUninitialized(dataType, shape, Nd4j.order(), Nd4j.getMemoryManager().getCurrentWorkspace());
@@ -5635,8 +5705,9 @@ public class Nd4j {
      *
      * @param arrs the first matrix to concat
      */
-    public static INDArray hstack(INDArray... arrs) {
-        return INSTANCE.hstack(arrs);
+    public static INDArray hstack(@NonNull INDArray... arrs) {
+        INDArray ret = INSTANCE.hstack(arrs);
+        return ret;
     }
 
     /**
@@ -5656,7 +5727,7 @@ public class Nd4j {
      *
      * @param arrs Arrays to vstack
      */
-    public static INDArray vstack(INDArray... arrs) {
+    public static INDArray vstack(@NonNull INDArray... arrs) {
         Preconditions.checkState(arrs != null && arrs.length > 0, "No input specified to vstack (null or length 0)");
         if(arrs[0].rank() == 1){
             //Edge case: vstack rank 1 arrays - gives rank 2... vstack([3],[3]) -> [2,3]
@@ -5758,7 +5829,7 @@ public class Nd4j {
      * @param arrays
      * @return
      */
-    public static INDArray accumulate(INDArray... arrays) {
+    public static INDArray accumulate(@NonNull INDArray... arrays) {
         if (arrays == null|| arrays.length == 0)
             throw new ND4JIllegalStateException("Input for accumulation is null or empty");
 
@@ -5798,7 +5869,7 @@ public class Nd4j {
      * @param indexes indexes from source array
      * @return
      */
-    public static INDArray pullRows(INDArray source, int sourceDimension, int[] indexes) {
+    public static INDArray pullRows(INDArray source, int sourceDimension, @NonNull int... indexes) {
         return pullRows(source, sourceDimension, indexes, Nd4j.order());
     }
 
@@ -5847,7 +5918,7 @@ public class Nd4j {
      * @param indexes indexes from source array
      * @return Destination array with specified tensors
      */
-    public static INDArray pullRows(INDArray source, INDArray destination, int sourceDimension, int[] indexes){
+    public static INDArray pullRows(INDArray source, INDArray destination, int sourceDimension, @NonNull int... indexes){
         if (sourceDimension >= source.rank())
             throw new IllegalStateException("Source dimension can't be higher the rank of source tensor");
 
@@ -5880,7 +5951,7 @@ public class Nd4j {
      * @return Output array
      * @see #concat(int, INDArray...)
      */
-    public static INDArray stack(int axis, INDArray... values){
+    public static INDArray stack(int axis, @NonNull INDArray... values){
         Preconditions.checkArgument(values != null && values.length > 0, "No inputs: %s", values);
         Preconditions.checkState(axis >= -(values[0].rank()+1) && axis < values[0].rank()+1, "Invalid axis: must be between " +
                 "%s (inclusive) and %s (exclusive) for rank %s input, got %s", -(values[0].rank()+1), values[0].rank()+1,
@@ -5902,7 +5973,7 @@ public class Nd4j {
      * the ndarray shapes save the dimension shape specified
      * which is then the sum of the sizes along that dimension
      */
-    public static INDArray concat(int dimension, INDArray... toConcat) {
+    public static INDArray concat(int dimension, @NonNull INDArray... toConcat) {
         if(dimension < 0) {
             dimension += toConcat[0].rank();
         }
@@ -5919,8 +5990,9 @@ public class Nd4j {
      * @param toConcat
      * @return
      */
-    public static INDArray specialConcat(int dimension, INDArray... toConcat) {
-        return  INSTANCE.specialConcat(dimension, toConcat);
+    public static INDArray specialConcat(int dimension, @NonNull INDArray... toConcat) {
+        INDArray ret = INSTANCE.specialConcat(dimension, toConcat);
+        return ret;
     }
 
     /**
@@ -5950,7 +6022,7 @@ public class Nd4j {
      * @param shape the shape of the array
      * @return an ndarray with ones filled in
      */
-    public static INDArray zeros(int... shape) {
+    public static INDArray zeros(@NonNull int... shape) {
         return Nd4j.create(shape);
     }
 
@@ -5961,7 +6033,7 @@ public class Nd4j {
      * @param shape the shape of the array
      * @return an ndarray with ones filled in
      */
-    public static INDArray zeros(long... shape) {
+    public static INDArray zeros(@NonNull long... shape) {
         return Nd4j.create(shape);
     }
 
@@ -6085,7 +6157,7 @@ public class Nd4j {
      * @return the strides for the given shape
      * and order specified by NDArrays.order()
      */
-    public static int[] getStrides(int[] shape) {
+    public static int[] getStrides(@NonNull int... shape) {
         return getStrides(shape, Nd4j.order());
     }
 
@@ -6097,7 +6169,7 @@ public class Nd4j {
      * @return the strides for the given shape
      * and order specified by NDArrays.order()
      */
-    public static long[] getStrides(long[] shape) {
+    public static long[] getStrides(@NonNull long... shape) {
         return getStrides(shape, Nd4j.order());
     }
 
@@ -6108,7 +6180,7 @@ public class Nd4j {
      * @param repeat the shape to repeat
      * @return the tiled ndarray
      */
-    public static INDArray tile(INDArray tile, int... repeat) {
+    public static INDArray tile(INDArray tile, @NonNull int... repeat) {
         int d = repeat.length;
         long[] shape = ArrayUtil.copy(tile.shape());
         long n = Math.max(tile.length(), 1);
@@ -6157,11 +6229,11 @@ public class Nd4j {
      * @return the strides for the given shape
      * and order specified by NDArrays.order()
      */
-    public static int[] getComplexStrides(int[] shape) {
+    public static int[] getComplexStrides(@NonNull int... shape) {
         return getComplexStrides(shape, Nd4j.order());
     }
 
-    public static long[] getComplexStrides(long[] shape) {
+    public static long[] getComplexStrides(@NonNull long... shape) {
         return getComplexStrides(shape, Nd4j.order());
     }
 
@@ -6501,7 +6573,7 @@ public class Nd4j {
      *
      * @return
      */
-    public static INDArray pile(INDArray... arrays) {
+    public static INDArray pile(@NonNull INDArray... arrays) {
         // if we have vectors as input, it's just vstack use case
 
         long[] shape = arrays[0].shape();
@@ -6536,7 +6608,7 @@ public class Nd4j {
      * @param dimensions
      * @return
      */
-    public static INDArray[] tear(INDArray tensor, int... dimensions) {
+    public static INDArray[] tear(INDArray tensor, @NonNull int... dimensions) {
         if (dimensions.length >= tensor.rank())
             throw new ND4JIllegalStateException("Target dimensions number should be less tensor rank");
 

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/string/NDArrayStrings.java

@@ -40,6 +40,8 @@ import java.util.Locale;
  * @author Adam Gibson
  * @author Susan Eraly
  */
+@Getter
+@Setter
 public class NDArrayStrings {
 
     public static final String EMPTY_ARRAY_STR = "[]";
@@ -55,7 +57,7 @@ public class NDArrayStrings {
     @Setter @Getter
     private static long maxPrintElements = DEFAULT_MAX_PRINT_ELEMENTS;
 
-
+    private long localMaxPrintElements = maxPrintElements;
     private String colSep = ",";
     private String newLineSep = ",";
     private int padding = 7;
@@ -82,6 +84,38 @@ public class NDArrayStrings {
         this(",", precision);
     }
 
+    public NDArrayStrings(long maxElements, int precision) {
+        this(",", precision);
+        this.localMaxPrintElements = maxElements;
+    }
+
+    public NDArrayStrings(long maxElements) {
+        this();
+        this.localMaxPrintElements = maxElements;
+    }
+
+    public NDArrayStrings(long maxElements, boolean forceSummarize, int precision) {
+        this(",", precision);
+        if(forceSummarize)
+            localMaxPrintElements = 0;
+        else
+            localMaxPrintElements = maxElements;
+    }
+
+    public NDArrayStrings(boolean forceSummarize, int precision) {
+        this(",", precision);
+        if(forceSummarize)
+            localMaxPrintElements = 0;
+    }
+
+
+
+    public NDArrayStrings(boolean forceSummarize) {
+        this(",", 4);
+        if(forceSummarize)
+            localMaxPrintElements = 0;
+    }
+
 
     /**
      * Specify a delimiter for elements in columns for 2d arrays (or in the rank-1th dimension in higher order arrays)
@@ -93,13 +127,17 @@ public class NDArrayStrings {
     public NDArrayStrings(String colSep, int precision) {
         this.colSep = colSep;
         if (!colSep.replaceAll("\\s", "").equals(",")) this.newLineSep = "";
-        this.precision = precision;
-        String decFormatNum = "0.";
-        while (precision > 0) {
-            decFormatNum += "0";
-            precision -= 1;
+        StringBuilder decFormatNum = new StringBuilder("0.");
+
+        int prec = Math.abs(precision);
+        this.precision = prec;
+        boolean useHash = precision < 0;
+
+        while (prec > 0) {
+            decFormatNum.append(useHash ? "#" : "0");
+            prec -= 1;
         }
-        this.decimalFormat = localeIndifferentDecimalFormat(decFormatNum);
+        this.decimalFormat = localeIndifferentDecimalFormat(decFormatNum.toString());
     }
 
     /**
@@ -147,7 +185,7 @@ public class NDArrayStrings {
         if (this.scientificFormat.length() + 2  > this.padding) this.padding = this.scientificFormat.length() + 2;
         this.maxToPrintWithoutSwitching = Math.pow(10,this.precision);
         this.minToPrintWithoutSwitching = 1.0/(this.maxToPrintWithoutSwitching);
-        return format(arr, 0, summarize && arr.length() > maxPrintElements);
+        return format(arr, 0, summarize && arr.length() > localMaxPrintElements);
     }
 
     private String format(INDArray arr, int offset, boolean summarize) {

nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/linalg/ToStringTest.java

@@ -0,0 +1,65 @@
+/*******************************************************************************
+ * Copyright (c) 2015-2018 Skymind, Inc.
+ *
+ * This program and the accompanying materials are made available under the
+ * terms of the Apache License, Version 2.0 which is available at
+ * https://www.apache.org/licenses/LICENSE-2.0.
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
+ * License for the specific language governing permissions and limitations
+ * under the License.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ ******************************************************************************/
+
+package org.nd4j.linalg;
+
+import static org.junit.Assert.assertEquals;
+
+import java.io.ByteArrayInputStream;
+import java.io.ByteArrayOutputStream;
+import java.io.ObjectInputStream;
+import java.io.ObjectOutputStream;
+import lombok.extern.slf4j.Slf4j;
+import lombok.val;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Parameterized;
+import org.nd4j.linalg.api.buffer.DataType;
+import org.nd4j.linalg.api.ndarray.INDArray;
+import org.nd4j.linalg.factory.Nd4j;
+import org.nd4j.linalg.factory.Nd4jBackend;
+
+@RunWith(Parameterized.class)
+@Slf4j
+public class ToStringTest extends BaseNd4jTest {
+    public ToStringTest(Nd4jBackend backend) {
+        super(backend);
+    }
+
+    @Test
+    public void testToString() throws Exception {
+        assertEquals("[         1,         2,         3]",
+                Nd4j.createFromArray(1, 2, 3).toString());
+
+        assertEquals("[         1,         2,         3  ...         6         7,         8]",
+                Nd4j.createFromArray(1, 2, 3, 4, 5, 6, 7, 8).toString(1000, false, 2));
+
+        assertEquals("[    1.132,    2.644,    3.234]",
+                Nd4j.createFromArray(1.132414, 2.64356456, 3.234234).toString(1000, false, 3));
+
+        assertEquals("[               1.132414,             2.64356456,             3.25345234]",
+                Nd4j.createFromArray(1.132414, 2.64356456, 3.25345234).toStringFull());
+
+        assertEquals("[         1,         2,         3  ...         6         7,         8]",
+                Nd4j.createFromArray(1, 2, 3, 4, 5, 6, 7, 8).toString(100, true, 1));
+
+    }
+
+    @Override
+    public char ordering() {
+        return 'c';
+    }
+}

nd4j/nd4j-buffer/src/main/java/org/nd4j/linalg/api/buffer/DataType.java

@@ -124,6 +124,36 @@ public enum DataType {
         }
     }
 
+    /**
+     * @return the max number of significant decimal digits
+     */
+    public int precision(){
+        switch (this){
+            case DOUBLE:
+                return 17;
+            case FLOAT:
+                return 9;
+            case HALF:
+                return 5;
+            case BFLOAT16:
+                return 4;
+            case LONG:
+            case INT:
+            case SHORT:
+            case BYTE:
+            case UBYTE:
+            case BOOL:
+            case UTF8:
+            case COMPRESSED:
+            case UINT16:
+            case UINT32:
+            case UINT64:
+            case UNKNOWN:
+            default:
+                return -1;
+        }
+    }
+
     /**
      * @return For fixed-width types, this returns the number of bytes per array element
      */