From c64b340975ae4171dae0b1f9741f2fc62a13449c Mon Sep 17 00:00:00 2001 From: Robert Altena Date: Tue, 3 Sep 2019 13:06:42 +0900 Subject: [PATCH] javadoc (#225) Signed-off-by: Robert Altena --- .../nd4j/linalg/api/ndarray/BaseNDArray.java | 242 ------------------ .../linalg/api/ndarray/BaseSparseNDArray.java | 2 - .../org/nd4j/linalg/api/ndarray/INDArray.java | 20 +- 3 files changed, 15 insertions(+), 249 deletions(-) diff --git a/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseNDArray.java b/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseNDArray.java index 0d0af0788..ac642872c 100644 --- a/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseNDArray.java +++ b/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseNDArray.java @@ -1195,7 +1195,6 @@ public abstract class BaseNDArray implements INDArray, Iterable { } } - return this; } @@ -3089,12 +3088,6 @@ public abstract class BaseNDArray implements INDArray, Iterable { return mmuli(other, result); } - /** - * in place (element wise) division of two matrices - * - * @param other the second ndarray to divide - * @return the result of the divide - */ @Override public INDArray div(INDArray other) { if (Shape.areShapesBroadcastable(this.shape(), other.shape())) { @@ -3104,25 +3097,12 @@ public abstract class BaseNDArray implements INDArray, Iterable { } } - /** - * copy (element wise) division of two matrices - * - * @param other the second ndarray to divide - * @param result the result ndarray - * @return the result of the divide - */ @Override public INDArray div(INDArray other, INDArray result) { validateNumericalArray("div", true); return divi(other, result); } - /** - * copy (element wise) multiplication of two matrices - * - * @param other the second ndarray to multiply - * @return the result of the addition - */ @Override public INDArray mul(INDArray other) { validateNumericalArray("mul", false); @@ -3134,24 +3114,11 @@ public abstract class BaseNDArray implements INDArray, Iterable { } } - /** - * copy (element wise) multiplication of two matrices - * - * @param other the second ndarray to multiply - * @param result the result ndarray - * @return the result of the multiplication - */ @Override public INDArray mul(INDArray other, INDArray result) { return muli(other, result); } - /** - * copy subtraction of two matrices - * - * @param other the second ndarray to subtract - * @return the result of the addition - */ @Override public INDArray sub(INDArray other) { validateNumericalArray("sub", false); @@ -3162,24 +3129,11 @@ public abstract class BaseNDArray implements INDArray, Iterable { } } - /** - * copy subtraction of two matrices - * - * @param other the second ndarray to subtract - * @param result the result ndarray - * @return the result of the subtraction - */ @Override public INDArray sub(INDArray other, INDArray result) { return subi(other, result); } - /** - * copy addition of two matrices - * - * @param other the second ndarray to add - * @return the result of the addition - */ @Override public INDArray add(INDArray other) { validateNumericalArray("add", false); @@ -3190,65 +3144,29 @@ public abstract class BaseNDArray implements INDArray, Iterable { } } - /** - * copy addition of two matrices - * - * @param other the second ndarray to add - * @param result the result ndarray - * @return the result of the addition - */ @Override public INDArray add(INDArray other, INDArray result) { validateNumericalArray("add", false); return addi(other, result); } - - /** - * Perform an copy matrix multiplication - * - * @param other the other matrix to perform matrix multiply with - * @param transpose the transpose status of each ndarray - * @return the result of the matrix multiplication - */ @Override public INDArray mmuli(INDArray other, MMulTranspose transpose) { validateNumericalArray("mmuli", false); return dup().mmuli(other, this,transpose); } - /** - * Perform an copy matrix multiplication - * - * @param other the other matrix to perform matrix multiply with - * @return the result of the matrix multiplication - */ @Override public INDArray mmuli(INDArray other) { validateNumericalArray("mmuli", false); return dup().mmuli(other, this); } - - /** - * Perform an in place matrix multiplication - * - * @param other the other matrix to perform matrix multiply with - * @param result the result ndarray - * @return the result of the matrix multiplication - */ @Override public INDArray mmuli(INDArray other, INDArray result, MMulTranspose transpose) { return transpose.exec(this, other, result); } - /** - * Perform an copy matrix multiplication - * - * @param other the other matrix to perform matrix multiply with - * @param result the result ndarray - * @return the result of the matrix multiplication - */ @Override public INDArray mmuli(INDArray other, INDArray result) { validateNumericalArray("mmuli", false); @@ -3347,24 +3265,11 @@ public abstract class BaseNDArray implements INDArray, Iterable { return Nd4j.create(shape, stride); } - /** - * in place (element wise) division of two matrices - * - * @param other the second ndarray to divide - * @return the result of the divide - */ @Override public INDArray divi(INDArray other) { return divi(other, this); } - /** - * in place (element wise) division of two matrices - * - * @param other the second ndarray to divide - * @param result the result ndarray - * @return the result of the divide - */ @Override public INDArray divi(INDArray other, INDArray result) { validateNumericalArray("divi", false); @@ -3373,24 +3278,11 @@ public abstract class BaseNDArray implements INDArray, Iterable { return result; } - /** - * in place (element wise) multiplication of two matrices - * - * @param other the second ndarray to multiply - * @return the result of the multiplication - */ @Override public INDArray muli(INDArray other) { return muli(other, this); } - /** - * in place (element wise) multiplication of two matrices - * - * @param other the second ndarray to multiply - * @param result the result ndarray - * @return the result of the multiplication - */ @Override public INDArray muli(INDArray other, INDArray result) { validateNumericalArray("muli", false); @@ -3399,12 +3291,6 @@ public abstract class BaseNDArray implements INDArray, Iterable { return result; } - /** - * in place subtraction of two matrices - * - * @param other the second ndarray to subtract - * @return the result of the addition - */ @Override public INDArray subi(INDArray other) { return subi(other, this); @@ -3425,24 +3311,11 @@ public abstract class BaseNDArray implements INDArray, Iterable { return result; } - /** - * in place addition of two matrices - * - * @param other the second ndarray to add - * @return the result of the addition - */ @Override public INDArray addi(INDArray other) { return addi(other, this); } - /** - * in place addition of two matrices - * - * @param other the second ndarray to add - * @param result the result ndarray - * @return the result of the addition - */ @Override public INDArray addi(INDArray other, INDArray result) { validateNumericalArray("addi", false); @@ -3451,25 +3324,12 @@ public abstract class BaseNDArray implements INDArray, Iterable { return result; } - /** - * 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 - * - * @param dimension the dimension to getScalar the norm1 along - * @return the norm1 along the specified dimension - */ @Override public INDArray normmax(int... dimension) { return normmax(false, dimension); @@ -4071,49 +3931,23 @@ 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 - * - * @param dimension the dimension to getScalar the product along - * @return the product along the specified dimension - */ @Override public INDArray prod(int... dimension) { return prod(false, 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)); } - /** - * Returns the overall mean of this ndarray - * - * @param dimension the dimension to getScalar the mean along - * @return the mean along the specified dimension of this ndarray - */ @Override public INDArray mean(int... dimension) { return mean(false, dimension); @@ -4136,50 +3970,24 @@ public abstract class BaseNDArray implements INDArray, Iterable { return mean(result, false, dimension); } - /** - * Returns the overall variance of this ndarray - * - * @param dimension the dimension to getScalar the mean along - * @return the mean along the specified dimension of this ndarray - */ @Override public INDArray var(int... dimension) { validateNumericalArray("var", false); return Nd4j.getExecutioner().exec(new Variance(this, dimension)); } - /** - * 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 - * @return the mean along the specified dimension of this ndarray - */ @Override public INDArray var(boolean biasCorrected, int... dimension) { validateNumericalArray("var", false); 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 - * - * @param dimension the dimension to getScalar the mean along - * @return the mean along the specified dimension of this ndarray - */ @Override public INDArray max(int... dimension) { return max(false, dimension); @@ -4191,25 +3999,12 @@ 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 - * - * @param dimension the dimension to getScalar the mean along - * @return the mean along the specified dimension of this ndarray - */ @Override public INDArray min(int... dimension) { return min(false, dimension); @@ -4290,39 +4085,17 @@ public abstract class BaseNDArray implements INDArray, Iterable { return sum(result, false, dimension); } - - /** - * Returns the norm1 along the specified dimension - * - * @param dimension the dimension to getScalar the norm1 along - * @return the norm1 along the specified dimension - */ @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, keepDims, dimension)); } - - /** - * Standard deviation of an ndarray along a dimension - * - * @param dimension the dimension to getScalar the std along - * @return the standard deviation along a particular dimension - */ @Override public INDArray std(int... dimension) { return std(true, dimension); @@ -4345,32 +4118,17 @@ 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 - * - * @param dimension the dimension to getScalar the norm2 along - * @return the norm2 along the specified dimension - */ @Override public INDArray norm2(int... dimension) { return norm2(false, dimension); } - - /** * Number of columns (shape[1]), throws an exception when * called when not 2d diff --git a/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseSparseNDArray.java b/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseSparseNDArray.java index 6a112b868..1e0772494 100644 --- a/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseSparseNDArray.java +++ b/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/BaseSparseNDArray.java @@ -1232,8 +1232,6 @@ public abstract class BaseSparseNDArray implements ISparseNDArray { return null; } - - @Override public INDArray normmax(boolean keepDims, int... dimension) { return null; diff --git a/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/INDArray.java b/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/INDArray.java index b842797f9..47e259b94 100644 --- a/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/INDArray.java +++ b/nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ndarray/INDArray.java @@ -1404,7 +1404,13 @@ public interface INDArray extends Serializable, AutoCloseable { */ INDArray add(INDArray other, INDArray result); - + /** + * Perform an copy matrix multiplication + * + * @param other the other matrix to perform matrix multiply with + * @param transpose the transpose status of each ndarray + * @return the result of the matrix multiplication + */ INDArray mmuli(INDArray other, MMulTranspose transpose); /** @@ -1415,7 +1421,13 @@ public interface INDArray extends Serializable, AutoCloseable { */ INDArray mmuli(INDArray other); - + /** + * Perform an in place matrix multiplication + * + * @param other the other matrix to perform matrix multiply with + * @param result the result ndarray + * @return the result of the matrix multiplication + */ INDArray mmuli(INDArray other, INDArray result, MMulTranspose transpose); /** @@ -1497,7 +1509,6 @@ public interface INDArray extends Serializable, AutoCloseable { */ INDArray addi(INDArray other, INDArray result); - /** * Returns the max norm (aka infinity norm, equal to the maximum absolute value) along the specified dimension(s) * @@ -1506,7 +1517,6 @@ 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) * @@ -1585,7 +1595,7 @@ public interface INDArray extends Serializable, AutoCloseable { /** * Calculate the standard deviation for the entire array * - * @return + * @return standard deviation */ Number stdNumber();