added keepDims to INDArray methods (#33)

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

@@ -3879,6 +3879,19 @@ public abstract class BaseNDArray implements INDArray, Iterable {
         }
     }
 
+    /**
+     * Returns the normmax along the specified dimension
+     *
+     * @param dimension the dimension to getScalar the norm1 along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the norm1 along the specified dimension
+     */
+    @Override
+    public INDArray normmax(boolean keepDims, int... dimension) {
+        validateNumericalArray("normmax", false);
+        return Nd4j.getExecutioner().exec(new NormMax(this, keepDims, dimension));
+    }
+
     /**
      * Returns the normmax along the specified dimension
      *
@@ -3887,8 +3900,7 @@ public abstract class BaseNDArray implements INDArray, Iterable {
      */
     @Override
     public INDArray normmax(int... dimension) {
-        validateNumericalArray("normmax", false);
+        return normmax(false, dimension);
-        return Nd4j.getExecutioner().exec(new NormMax(this, dimension));
     }
 
     /**
@@ -4608,6 +4620,19 @@ public abstract class BaseNDArray implements INDArray, Iterable {
         return reshape(Nd4j.order(), shape);
     }
 
+    /**
+     * Returns the product along a given dimension
+     *
+     * @param dimension the dimension to getScalar the product along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the product along the specified dimension
+     */
+    @Override
+    public INDArray prod(boolean keepDims, int... dimension) {
+        validateNumericalArray("prod", false);
+        return Nd4j.getExecutioner().exec(new Prod(this, keepDims, dimension));
+    }
+
     /**
      * Returns the product along a given dimension
      *
@@ -4616,8 +4641,20 @@ public abstract class BaseNDArray implements INDArray, Iterable {
      */
     @Override
     public INDArray prod(int... dimension) {
-        validateNumericalArray("prod", false);
+        return prod(false, dimension);
-        return Nd4j.getExecutioner().exec(new Prod(this, dimension));
+    }
+
+    /**
+     * Returns the overall mean of this ndarray
+     *
+     * @param dimension the dimension to getScalar the mean along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the mean along the specified dimension of this ndarray
+     */
+    @Override
+    public INDArray mean(boolean keepDims, int... dimension) {
+        validateNumericalArray("mean", false);
+        return Nd4j.getExecutioner().exec(new Mean(this, keepDims, dimension));
     }
 
     /**
@@ -4628,8 +4665,7 @@ public abstract class BaseNDArray implements INDArray, Iterable {
      */
     @Override
     public INDArray mean(int... dimension) {
-        validateNumericalArray("mean", false);
+        return mean(false, dimension);
-        return Nd4j.getExecutioner().exec(new Mean(this, dimension));
     }
 
     @Override
@@ -4639,9 +4675,14 @@ public abstract class BaseNDArray implements INDArray, Iterable {
     }
 
     @Override
-    public INDArray mean(@NonNull INDArray result, int... dimension) {
+    public INDArray mean(@NonNull INDArray result, boolean keepDims, int... dimension) {
         validateNumericalArray("mean", false);
-        return Nd4j.getExecutioner().exec(new Mean(this, result, dimension));
+        return Nd4j.getExecutioner().exec(new Mean(this, result, keepDims, dimension));
+    }
+
+    @Override
+    public INDArray mean(@NonNull INDArray result, int... dimension) {
+        return mean(result, false, dimension);
     }
 
     /**
@@ -4669,6 +4710,19 @@ public abstract class BaseNDArray implements INDArray, Iterable {
         return Nd4j.getExecutioner().exec(new Variance(this, biasCorrected, dimension));
     }
 
+    /**
+     * Returns the overall max of this ndarray
+     *
+     * @param dimension the dimension to getScalar the mean along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the mean along the specified dimension of this ndarray
+     */
+    @Override
+    public INDArray max(boolean keepDims, int... dimension) {
+        validateNumericalArray("max", false);
+        return Nd4j.getExecutioner().exec(new Max(this, keepDims, dimension));
+    }
+
     /**
      * Returns the overall max of this ndarray
      *
@@ -4677,8 +4731,7 @@ public abstract class BaseNDArray implements INDArray, Iterable {
      */
     @Override
     public INDArray max(int... dimension) {
-        validateNumericalArray("max", false);
+        return max(false, dimension);
-        return Nd4j.getExecutioner().exec(new Max(this, dimension));
     }
 
     @Override
@@ -4687,6 +4740,19 @@ public abstract class BaseNDArray implements INDArray, Iterable {
         return Nd4j.getExecutioner().exec(new AMax(this, dimension));
     }
 
+    /**
+     * Returns the overall min of this ndarray
+     *
+     * @param dimension the dimension to getScalar the mean along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the mean along the specified dimension of this ndarray
+     */
+    @Override
+    public INDArray min(boolean keepDims, int... dimension) {
+        validateNumericalArray("min", false);
+        return Nd4j.getExecutioner().exec(new Min(this, keepDims, dimension));
+    }
+
     /**
      * Returns the overall min of this ndarray
      *
@@ -4695,8 +4761,7 @@ public abstract class BaseNDArray implements INDArray, Iterable {
      */
     @Override
     public INDArray min(int... dimension) {
-        validateNumericalArray("min", false);
+        return min(false, dimension);
-        return Nd4j.getExecutioner().exec(new Min(this, dimension));
     }
 
     @Override
@@ -4764,9 +4829,14 @@ public abstract class BaseNDArray implements INDArray, Iterable {
     }
 
     @Override
-    public INDArray sum(@NonNull INDArray result, int... dimension) {
+    public INDArray sum(@NonNull INDArray result, boolean keepDims, int... dimension) {
         validateNumericalArray("sum", true);
-        return Nd4j.getExecutioner().exec(new Sum(this, result, dimension));
+        return Nd4j.getExecutioner().exec(new Sum(this, result, keepDims, dimension));
+    }
+
+    @Override
+    public INDArray sum(@NonNull INDArray result, int... dimension) {
+        return sum(result, false, dimension);
     }
 
 
@@ -4778,8 +4848,21 @@ public abstract class BaseNDArray implements INDArray, Iterable {
      */
     @Override
     public INDArray norm1(int... dimension) {
+        return norm1(false, dimension);
+    }
+
+
+    /**
+     * Returns the norm1 along the specified dimension
+     *
+     * @param dimension the dimension to getScalar the norm1 along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the norm1 along the specified dimension
+     */
+    @Override
+    public INDArray norm1(boolean keepDims, int... dimension) {
         validateNumericalArray("norm1", false);
-        return Nd4j.getExecutioner().exec(new Norm1(this, dimension));
+        return Nd4j.getExecutioner().exec(new Norm1(this, keepDims, dimension));
     }
 
 
@@ -4796,8 +4879,13 @@ public abstract class BaseNDArray implements INDArray, Iterable {
 
     @Override
     public INDArray std(boolean biasCorrected, int... dimension) {
+        return std(biasCorrected, false, dimension);
+    }
+
+    @Override
+    public INDArray std(boolean biasCorrected, boolean keepDims, int... dimension) {
         validateNumericalArray("std", false);
-        return Nd4j.getExecutioner().exec(new StandardDeviation(this, biasCorrected, dimension));
+        return Nd4j.getExecutioner().exec(new StandardDeviation(this, biasCorrected, keepDims, dimension));
     }
 
     @Override
@@ -4806,6 +4894,19 @@ public abstract class BaseNDArray implements INDArray, Iterable {
         return Nd4j.getExecutioner().exec(new StandardDeviation(this, biasCorrected)).getDouble(0);
     }
 
+    /**
+     * Returns the norm2 along the specified dimension
+     *
+     * @param dimension the dimension to getScalar the norm2 along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the norm2 along the specified dimension
+     */
+    @Override
+    public INDArray norm2(boolean keepDims, int... dimension) {
+        validateNumericalArray("norm2", false);
+        return Nd4j.getExecutioner().exec(new Norm2(this, keepDims, dimension));
+    }
+
     /**
      * Returns the norm2 along the specified dimension
      *
@@ -4814,8 +4915,7 @@ public abstract class BaseNDArray implements INDArray, Iterable {
      */
     @Override
     public INDArray norm2(int... dimension) {
-        validateNumericalArray("norm2", false);
+        return norm2(false, dimension);
-        return Nd4j.getExecutioner().exec(new Norm2(this, dimension));
     }
 
 

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

@@ -1250,6 +1250,58 @@ public abstract class BaseSparseNDArray implements ISparseNDArray {
         return null;
     }
 
+
+
+    @Override
+    public INDArray normmax(boolean keepDims, int... dimension) {
+        return null;
+    }
+
+    @Override
+    public INDArray norm2(boolean keepDims, int... dimension) {
+        return null;
+    }
+
+    @Override
+    public INDArray norm1(boolean keepDims, int... dimension) {
+        return null;
+    }
+
+    @Override
+    public INDArray std(boolean biasCorrected, boolean keepDims, int... dimension) {
+        return null;
+    }
+
+    @Override
+    public INDArray prod(boolean keepDims, int... dimension) {
+        return null;
+    }
+
+    @Override
+    public INDArray mean(boolean keepDims, int... dimension) {
+        return null;
+    }
+
+    @Override
+    public INDArray mean(INDArray result, boolean keepDims, int... dimension) {
+        return null;
+    }
+
+    @Override
+    public INDArray max(boolean keepDims, int... dimension) {
+        return null;
+    }
+
+    @Override
+    public INDArray min(boolean keepDims, int... dimension) {
+        return null;
+    }
+
+    @Override
+    public INDArray sum(INDArray result, boolean keepDims, int... dimension) {
+        return null;
+    }
+
     @Override
     public void setShapeAndStride(int[] shape, int[] stride) {
 

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

@@ -1518,6 +1518,16 @@ public interface INDArray extends Serializable, AutoCloseable {
      */
     INDArray normmax(int... dimension);
 
+
+    /**
+     * Returns the max norm (aka infinity norm, equal to the maximum absolute value) along the specified dimension(s)
+     *
+     * @param dimension the dimension to the max norm along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return Max norm along the specified dimension
+     */
+    INDArray normmax(boolean keepDims, int... dimension);
+
     /**
      * Return the max norm (aka infinity norm, equal to the maximum absolute value) for the entire array
      *
@@ -1533,6 +1543,15 @@ public interface INDArray extends Serializable, AutoCloseable {
      */
     INDArray norm2(int... dimension);
 
+    /**
+     * Returns the norm2 (L2 norm, sqrt(sum(x_i^2), also known as Euclidean norm) along the specified dimension(s)
+     *
+     * @param dimension the dimension to getScalar the norm2 along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the norm2 along the specified dimension
+     */
+    INDArray norm2(boolean keepDims, int... dimension);
+
     /**
      * Return the norm2 (L2 norm, sqrt(sum(x_i^2), also known as Euclidean norm) for the entire array
      *
@@ -1549,6 +1568,16 @@ public interface INDArray extends Serializable, AutoCloseable {
      */
     INDArray norm1(int... dimension);
 
+    /**
+     * Returns the norm1 (L1 norm, i.e., sum of absolute values; also known as Taxicab or Manhattan norm) along the
+     * specified dimension
+     *
+     * @param dimension the dimension to getScalar the norm1 along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the norm1 along the specified dimension
+     */
+    INDArray norm1(boolean keepDims, int... dimension);
+
     /**
      * Calculate and return norm1 (L1 norm, i.e., sum of absolute values; also known as Taxicab or Manhattan norm) for
      * the entire array
@@ -1580,6 +1609,15 @@ public interface INDArray extends Serializable, AutoCloseable {
      */
     INDArray std(boolean biasCorrected, int... dimension);
 
+    /**
+     * Standard deviation of an ndarray along a dimension
+     *
+     * @param dimension the dimension to getScalar the std along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the standard deviation along a particular dimension
+     */
+    INDArray std(boolean biasCorrected, boolean keepDims, int... dimension);
+
     /**
      * Calculate the standard deviation for the entire array, specifying whether it is bias corrected or not
      *
@@ -1596,6 +1634,15 @@ public interface INDArray extends Serializable, AutoCloseable {
      */
     INDArray prod(int... dimension);
 
+    /**
+     * Returns the product along a given dimension
+     *
+     * @param dimension the dimension to getScalar the product along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the product along the specified dimension
+     */
+    INDArray prod(boolean keepDims, int... dimension);
+
     /**
      * Calculate the product of all values in the array
      *
@@ -1619,11 +1666,29 @@ public interface INDArray extends Serializable, AutoCloseable {
      */
     INDArray mean(INDArray result, int... dimension);
 
+    /**
+     * Returns the overall mean of this ndarray
+     *
+     * @param dimension the dimension to getScalar the mean along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the mean along the specified dimension of this ndarray
+     */
+    INDArray mean(boolean keepDims, int... dimension);
+
+    /**
+     * Returns the overall mean of this ndarray
+     *
+     * @param dimension the dimension to getScalar the mean along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the mean along the specified dimension of this ndarray
+     */
+    INDArray mean(INDArray result, boolean keepDims, int... dimension);
+
     /**
      * Returns the absolute overall mean of this ndarray
      *
      * @param dimension the dimension to getScalar the mean along
-     * @return the mean along the specified dimension of this ndarray
+     * @return the absolute mean along the specified dimension of this ndarray
      */
     INDArray amean(int... dimension);
 
@@ -1644,8 +1709,8 @@ public interface INDArray extends Serializable, AutoCloseable {
     /**
      * Returns the overall variance of this ndarray
      *
-     * @param dimension the dimension to getScalar the mean along
+     * @param dimension the dimension to getScalar the variance along
-     * @return the mean along the specified dimension of this ndarray
+     * @return the variance along the specified dimension of this ndarray
      */
     INDArray var(int... dimension);
 
@@ -1653,8 +1718,8 @@ public interface INDArray extends Serializable, AutoCloseable {
      * Returns the overall variance of this ndarray
      *
      * @param biasCorrected boolean on whether to apply corrected bias
-     * @param dimension the dimension to getScalar the mean along
+     * @param dimension the dimension to getScalar the variance along
-     * @return the mean along the specified dimension of this ndarray
+     * @return the variance along the specified dimension of this ndarray
      */
     INDArray var(boolean biasCorrected, int... dimension);
 
@@ -1668,16 +1733,25 @@ public interface INDArray extends Serializable, AutoCloseable {
     /**
      * Returns the overall max of this ndarray along given dimensions
      *
-     * @param dimension the dimension to getScalar the mean along
+     * @param dimension the dimension to getScalar the max along
-     * @return the mean along the specified dimension of this ndarray
+     * @return the max along the specified dimension of this ndarray
      */
     INDArray max(int... dimension);
 
+    /**
+     * Returns the overall max of this ndarray along given dimensions
+     *
+     * @param dimension the dimension to getScalar the max along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the max along the specified dimension of this ndarray
+     */
+    INDArray max(boolean keepDims, int... dimension);
+
     /**
      * Returns the absolute overall max of this ndarray along given dimensions
      *
-     * @param dimension the dimension to getScalar the mean along
+     * @param dimension the dimension to getScalar the amax along
-     * @return the mean along the specified dimension of this ndarray
+     * @return the amax along the specified dimension of this ndarray
      */
     INDArray amax(int... dimension);
 
@@ -1696,11 +1770,20 @@ public interface INDArray extends Serializable, AutoCloseable {
     /**
      * Returns the overall min of this ndarray
      *
-     * @param dimension the dimension to getScalar the mean along
+     * @param dimension the dimension to getScalar the min along
-     * @return the mean along the specified dimension of this ndarray
+     * @return the min along the specified dimension of this ndarray
      */
     INDArray min(int... dimension);
 
+    /**
+     * Returns the overall min of this ndarray
+     *
+     * @param dimension the dimension to getScalar the min along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the min along the specified dimension of this ndarray
+     */
+    INDArray min(boolean keepDims, int... dimension);
+
     /**
      * Returns minimum (absolute) value in this INDArray, along the specified dimensions
      *
@@ -1729,6 +1812,13 @@ public interface INDArray extends Serializable, AutoCloseable {
      */
     INDArray sum(int... dimension);
 
+    /**
+     * Returns the sum along the last dimension of this ndarray
+     *
+     * @param dimension the dimension to getScalar the sum along
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @return the sum along the specified dimension of this ndarray
+     */
     INDArray sum(boolean keepDims, int... dimension);
 
     /**
@@ -1748,6 +1838,16 @@ public interface INDArray extends Serializable, AutoCloseable {
      */
     INDArray sum(INDArray result, int... dimension);
 
+    /**
+     * Returns the sum along the last dimension of this ndarray
+     *
+     * @param result result of this operation will be stored here
+     * @param keepDims whether to keep reduced dimensions as dimensions of size 1
+     * @param dimension the dimension to getScalar the sum along
+     * @return the sum along the specified dimension of this ndarray
+     */
+    INDArray sum(INDArray result, boolean keepDims, int... dimension);
+
     /**
      * Sum the entire array
      * @return Sum of array

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/BaseReduceFloatOp.java

@@ -69,6 +69,11 @@ public abstract class BaseReduceFloatOp extends BaseReduceOp implements ReduceFl
     }
 
 
+    public BaseReduceFloatOp(INDArray x, boolean keepDims, int... dimensions) {
+        super(x, keepDims, dimensions);
+    }
+
+
     public BaseReduceFloatOp(INDArray x, int... dimensions) {
         super(x, dimensions);
     }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/BaseReduceOp.java

@@ -144,6 +144,11 @@ public abstract class BaseReduceOp extends BaseOp implements ReduceOp {
         this(x, null, dimensions);
     }
 
+    public BaseReduceOp(INDArray x, boolean keepDims, int... dimensions) {
+        this(x, null, dimensions);
+        this.keepDims = keepDims;
+    }
+
     public BaseReduceOp(INDArray x, INDArray y, int... dimensions) {
         this(x, y, null, dimensions);
     }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/BaseReduceSameOp.java

@@ -58,6 +58,10 @@ public abstract class BaseReduceSameOp extends BaseReduceOp implements ReduceSam
         super(x, dimensions);
     }
 
+    public BaseReduceSameOp(INDArray x, boolean keepDims, int... dimensions) {
+        super(x, keepDims, dimensions);
+    }
+
     protected BaseReduceSameOp() {
         super();
     }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/reduce/floating/Mean.java

@@ -45,6 +45,10 @@ public class Mean extends BaseReduceFloatOp {
         super(x, dimensions);
     }
 
+    public Mean(INDArray x, boolean keepDims, int... dimensions) {
+        super(x, keepDims, dimensions);
+    }
+
     public Mean(INDArray x, INDArray z, boolean keepDims, int... dimensions) {
         super(x, z, keepDims, dimensions);
     }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/reduce/floating/Norm1.java

@@ -47,6 +47,10 @@ public class Norm1 extends BaseReduceFloatOp {
         super(x, dimensions);
     }
 
+    public Norm1(INDArray x, boolean keepDims, int... dimensions) {
+        super(x, keepDims, dimensions);
+    }
+
     @Override
     public INDArray noOp() {
         return Transforms.abs(x());

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/reduce/floating/Norm2.java

@@ -47,6 +47,10 @@ public class Norm2 extends BaseReduceFloatOp {
         super(x, dimensions);
     }
 
+    public Norm2(INDArray x, boolean keepDims, int... dimensions) {
+        super(x, keepDims, dimensions);
+    }
+
     @Override
     public INDArray noOp() {
         return Transforms.abs(x());

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/reduce/floating/NormMax.java

@@ -52,6 +52,10 @@ public class NormMax extends BaseReduceFloatOp {
         super(x, dimensions);
     }
 
+    public NormMax(INDArray x, boolean keepDims, int... dimensions) {
+        super(x, keepDims, dimensions);
+    }
+
     @Override
     public INDArray noOp() {
         return Transforms.abs(x());

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/reduce/same/Max.java

@@ -54,6 +54,9 @@ public class Max extends BaseReduceSameOp {
     public Max(INDArray x, int... axis) {
         super(x, null, null, axis);
     }
+    public Max(INDArray x, boolean keepDims, int... axis) {
+        super(x, keepDims, axis);
+    }
 
     public Max(INDArray x, INDArray z, int... axis) {
         super(x, null, z, axis);

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/reduce/same/Min.java

@@ -41,6 +41,10 @@ public class Min extends BaseReduceSameOp {
         super(x, dimensions);
     }
 
+    public Min(INDArray x, boolean keepDims, int... dimensions) {
+        super(x, keepDims, dimensions);
+    }
+
     public Min(INDArray x, INDArray z, int... dimensions) {
         super(x, null, z, dimensions);
     }

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/reduce/same/Prod.java

@@ -18,6 +18,7 @@ package org.nd4j.linalg.api.ops.impl.reduce.same;
 
 import org.nd4j.autodiff.samediff.SDVariable;
 import org.nd4j.autodiff.samediff.SameDiff;
+import org.nd4j.linalg.api.ndarray.BaseNDArray;
 import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.api.ops.BaseReduceSameOp;
 
@@ -53,6 +54,10 @@ public class Prod extends BaseReduceSameOp {
         super(x, z, keepDims, dimensions);
     }
 
+    public Prod(INDArray x, boolean keepDims, int... dimensions) {
+        super(x, keepDims, dimensions);
+    }
+
 
     @Override
     public int opNum() {

nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/summarystats/StandardDeviation.java

@@ -39,6 +39,11 @@ public class StandardDeviation extends Variance {
         super(sameDiff, i_v, biasCorrected, keepDims, dimensions );
     }
 
+    public StandardDeviation(INDArray x, boolean biasCorrected, boolean keepDims, int... dimension) {
+        super(x, biasCorrected, dimension);
+        this.keepDims = keepDims;
+    }
+
     public StandardDeviation(INDArray x, boolean biasCorrected, int... dimension) {
         super(x, biasCorrected, dimension);
     }