ai.djl.ndarray.NDArrays Maven / Gradle / Ivy
/*
* Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
* with the License. A copy of the License is located at
*
* http://aws.amazon.com/apache2.0/
*
* or in the "license" file accompanying this file. This file 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.
*/
package ai.djl.ndarray;
import ai.djl.ndarray.types.Shape;
import java.util.Arrays;
/** This class contains various methods for manipulating NDArrays. */
public final class NDArrays {
private NDArrays() {}
private static void checkInputs(NDArray[] arrays) {
if (arrays == null || arrays.length < 2) {
throw new IllegalArgumentException("Passed in arrays must have at least one element");
}
if (arrays.length > 2
&& Arrays.stream(arrays).skip(1).anyMatch(array -> !arrays[0].shapeEquals(array))) {
throw new IllegalArgumentException("The shape of all inputs must be the same");
}
}
////////////////////////////////////////
// Operations: Element Comparison
////////////////////////////////////////
/**
* Returns {@code true} if all elements in {@link NDArray} a are equal to {@link NDArray} b.
*
* Examples
*
*
* jshell> NDArray array = manager.ones(new Shape(3));
* jshell> NDArrays.contentEquals(array, 1); // return true instead of boolean NDArray
* true
*
*
* @param a the {@link NDArray} to compare
* @param n the number to compare
* @return the boolean result
*/
public static boolean contentEquals(NDArray a, Number n) {
if (a == null) {
return false;
}
return a.contentEquals(n);
}
/**
* Returns {@code true} if all elements in {@link NDArray} a are equal to {@link NDArray} b.
*
* Examples
*
*
* jshell> NDArray array1 = manager.arange(6f).reshape(2, 3);
* jshell> NDArray array2 = manager.create(new float[] {0f, 1f, 2f, 3f, 4f, 5f}, new Shape(2, 3));
* jshell> NDArrays.contentEquals(array1, array2); // return true instead of boolean NDArray
* true
*
*
* @param a the {@link NDArray} to compare
* @param b the {@link NDArray} to compare
* @return the boolean result
*/
public static boolean contentEquals(NDArray a, NDArray b) {
return a.contentEquals(b);
}
/**
* Checks 2 {@link NDArray}s for equal shapes.
*
* Shapes are considered equal if:
*
*
* - Both {@link NDArray}s have equal rank, and
*
- size(0)...size(rank()-1) are equal for both {@link NDArray}s
*
*
* Examples
*
*
* jshell> NDArray array1 = manager.ones(new Shape(1, 2, 3));
* jshell> NDArray array2 = manager.create(new Shape(1, 2, 3));
* jshell> NDArrays.shapeEquals(array1, array2); // return true instead of boolean NDArray
* true
*
*
* @param a the {@link NDArray} to compare
* @param b the {@link NDArray} to compare
* @return {@code true} if the {@link Shape}s are the same
*/
public static boolean shapeEquals(NDArray a, NDArray b) {
return a.shapeEquals(b);
}
/**
* Returns {@code true} if two {@link NDArray} are element-wise equal within a tolerance.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new double[] {1e10,1e-7});
* jshell> NDArray array2 = manager.create(new double[] {1.00001e10,1e-8});
* jshell> NDArrays.allClose(array1, array2); // return false instead of boolean NDArray
* false
* jshell> NDArray array1 = manager.create(new double[] {1e10,1e-8});
* jshell> NDArray array2 = manager.create(new double[] {1.00001e10,1e-9});
* jshell> NDArrays.allClose(array1, array2); // return true instead of boolean NDArray
* true
*
*
* @param a the {@link NDArray} to compare with
* @param b the {@link NDArray} to compare with
* @return the boolean result
*/
public static boolean allClose(NDArray a, NDArray b) {
return a.allClose(b);
}
/**
* Returns {@code true} if two {@link NDArray} are element-wise equal within a tolerance.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new double[] {1e10, 1e-7});
* jshell> NDArray array2 = manager.create(new double[] {1.00001e10, 1e-8});
* jshell> NDArrays.allClose(array1, array2, 1e-05, 1e-08, false); // return false instead of boolean NDArray
* false
* jshell> NDArray array1 = manager.create(new double[] {1e10, 1e-8});
* jshell> NDArray array2 = manager.create(new double[] {1.00001e10, 1e-9});
* jshell> NDArrays.allClose(array1, array2, 1e-05, 1e-08, false); // return true instead of boolean NDArray
* true
* jshell> NDArray array1 = manager.create(new float[] {1f, Float.NaN});
* jshell> NDArray array2 = manager.create(new float[] {1f, Float.NaN});
* jshell> NDArrays.allClose(array1, array2, 1e-05, 1e-08, true); // return true instead of boolean NDArray
* true
*
*
* @param a the {@link NDArray} to compare with
* @param b the {@link NDArray} to compare with
* @param rtol the relative tolerance parameter
* @param atol the absolute tolerance parameter
* @param equalNan whether to compare NaN’s as equal. If {@code true}, NaN’s in the {@link
* NDArray} will be considered equal to NaN’s in the other {@link NDArray}
* @return the boolean result
*/
public static boolean allClose(
NDArray a, NDArray b, double rtol, double atol, boolean equalNan) {
return a.allClose(b, rtol, atol, equalNan);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Equals" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.ones(new Shape(1));
* jshell> NDArrays.eq(array, 1);
* ND: (1) cpu() boolean
* [ true]
*
*
* @param a the {@link NDArray} to compare
* @param n the number to compare
* @return the boolean {@link NDArray} for element-wise "Equals" comparison
*/
public static NDArray eq(NDArray a, Number n) {
return a.eq(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Equals" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.ones(new Shape(1));
* jshell> NDArrays.eq(1, array);
* ND: (1) cpu() boolean
* [ true]
*
*
* @param n the number to compare
* @param a the {@link NDArray} to compare
* @return the boolean {@link NDArray} for element-wise "Equals" comparison
*/
public static NDArray eq(Number n, NDArray a) {
return a.eq(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Equals" comparison.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {0f, 1f, 3f});
* jshell> NDArray array2 = manager.arange(3f);
* jshell> NDArrays.eq(array1, array2);
* ND: (3) cpu() boolean
* [ true, true, false]
*
*
* @param a the {@link NDArray} to compare
* @param b the {@link NDArray} to compare
* @return the boolean {@link NDArray} for element-wise "Equals" comparison
*/
public static NDArray eq(NDArray a, NDArray b) {
return a.eq(b);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Not equals" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(4f).reshape(2, 2);
* jshell> NDArrays.neq(array, 1);
* ND: (2, 2) cpu() boolean
* [[ true, false],
* [ true, true],
* ]
*
*
* @param a the {@link NDArray} to compare
* @param n the number to compare
* @return the boolean {@link NDArray} for element-wise "Not equals" comparison
*/
public static NDArray neq(NDArray a, Number n) {
return a.neq(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Not equals" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(f4).reshape(2, 2);
* jshell> NDArrays.neq(1, array);
* ND: (2, 2) cpu() boolean
* [[ true, false],
* [ true, true],
* ]
*
*
* @param n the number to compare
* @param a the {@link NDArray} to compare
* @return the boolean {@link NDArray} for element-wise "Not equals" comparison
*/
public static NDArray neq(Number n, NDArray a) {
return a.neq(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Not equals" comparison.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {1f, 3f});
* jshell> NDArrays.neq(array1, array2);
* ND: (2) cpu() boolean
* [false, true]
* jshell> NDArray array1 = manager.create(new float[] {1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {1f, 3f, 1f, 4f}, new Shape(2, 2));
* jshell> NDArrays.neq(array1, array2); // broadcasting
* ND: (2, 2) cpu() boolean
* [[false, true],
* [false, true],
* ]
*
*
* @param a the {@link NDArray} to compare
* @param b the {@link NDArray} to compare
* @return the boolean {@link NDArray} for element-wise "Not equals" comparison
*/
public static NDArray neq(NDArray a, NDArray b) {
return a.neq(b);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Greater Than" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {4f, 2f});
* jshell> NDArrays.gt(array, 2f);
* ND: (2) cpu() boolean
* [ true, false]
*
*
* @param a the {@link NDArray} to compare
* @param n the number to be compared against
* @return the boolean {@link NDArray} for element-wise "Greater Than" comparison
*/
public static NDArray gt(NDArray a, Number n) {
return a.gt(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Greater Than" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {4f, 2f});
* jshell> NDArrays.gt(2f, array);
* ND: (2) cpu() boolean
* [false, false]
*
*
* @param n the number to be compared
* @param a the NDArray to be compared against
* @return the boolean {@link NDArray} for element-wise "Greater Than" comparison
*/
public static NDArray gt(Number n, NDArray a) {
return a.lt(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Greater Than" comparison.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {4f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {2f, 2f});
* jshell> NDArrays.gt(array1, array2);
* ND: (2) cpu() boolean
* [ true, false]
*
*
* @param a the {@link NDArray} to be compared
* @param b the {@link NDArray} to be compared against
* @return the boolean {@link NDArray} for element-wise "Greater Than" comparison
*/
public static NDArray gt(NDArray a, NDArray b) {
return a.gt(b);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Greater or equals" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {4f, 2f});
* jshell> NDArrays.gte(array, 2);
* ND: (2) cpu() boolean
* [ true, true]
*
*
* @param a the {@link NDArray} to be compared
* @param n the number to be compared against
* @return the boolean {@link NDArray} for element-wise "Greater or equals" comparison
*/
public static NDArray gte(NDArray a, Number n) {
return a.gte(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Greater or equals" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {4f, 2f});
* jshell> NDArrays.gte(2, array);
* ND: (2) cpu() boolean
* [false, true]
*
*
* @param n the number to be compared
* @param a the {@link NDArray} to be compared against
* @return the boolean {@link NDArray} for element-wise "Greater or equals" comparison
*/
public static NDArray gte(Number n, NDArray a) {
return a.lte(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Greater or equals" comparison.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {4f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {2f, 2f});
* jshell> NDArrays.gte(array1, array2);
* ND: (2) cpu() boolean
* [ true, true]
*
*
* @param a the {@link NDArray} to be compared
* @param b the {@link NDArray} to be compared against
* @return the boolean {@link NDArray} for element-wise "Greater or equals" comparison
*/
public static NDArray gte(NDArray a, NDArray b) {
return a.gte(b);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Less" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.lt(array, 2f);
* ND: (2) cpu() boolean
* [ true, false]
*
*
* @param a the {@link NDArray} to be compared
* @param n the number to be compared against
* @return the boolean {@link NDArray} for element-wise "Less" comparison
*/
public static NDArray lt(NDArray a, Number n) {
return a.lt(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Less" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.lt(2f, array);
* ND: (2) cpu() boolean
* [false, false]
*
*
* @param n the number to be compared
* @param a the {@link NDArray} to be compared against
* @return the boolean {@link NDArray} for element-wise "Less" comparison
*/
public static NDArray lt(Number n, NDArray a) {
return a.gt(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Less" comparison.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {2f, 2f});
* jshell> NDArrays.lt(array1, array2);
* ND: (2) cpu() boolean
* [ true, false]
*
*
* @param a the {@link NDArray} to be compared
* @param b the {@link NDArray} to be compared against
* @return the boolean {@link NDArray} for element-wise "Less" comparison
*/
public static NDArray lt(NDArray a, NDArray b) {
return a.lt(b);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Less or equals" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.lte(array, 2f);
* ND: (2) cpu() boolean
* [ true, true]
*
*
* @param a the {@link NDArray} to be compared
* @param n the number to be compared against
* @return the boolean {@link NDArray} for element-wise "Less or equals" comparison
*/
public static NDArray lte(NDArray a, Number n) {
return a.lte(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Less or equals" comparison.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.lte(2f, array);
* ND: (2) cpu() boolean
* [false, true]
*
*
* @param n the number to be compared
* @param a the {@link NDArray} to be compared against
* @return the boolean {@link NDArray} for element-wise "Less or equals" comparison
*/
public static NDArray lte(Number n, NDArray a) {
return a.gte(n);
}
/**
* Returns the boolean {@link NDArray} for element-wise "Less or equals" comparison.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {2f, 2f});
* jshell> NDArrays.lte(array1, array2)
* ND: (2) cpu() boolean
* [ true, true]
*
*
* @param a the {@link NDArray} to be compared
* @param b the {@link NDArray} to be compared against
* @return the boolean {@link NDArray} for element-wise "Less or equals" comparison
*/
public static NDArray lte(NDArray a, NDArray b) {
return a.lte(b);
}
/**
* Returns elements chosen from the {@link NDArray} or the other {@link NDArray} depending on
* condition.
*
* Given three {@link NDArray}s, condition, a, and b, returns an {@link NDArray} with the
* elements from a or b, depending on whether the elements from condition {@link NDArray} are
* {@code true} or {@code false}. If condition has the same shape as a, each element in the
* output {@link NDArray} is from this if the corresponding element in the condition is {@code
* true}, and from other if {@code false}.
*
*
Note that all non-zero values are interpreted as {@code true} in condition {@link
* NDArray}.
*
*
Examples
*
*
* jshell> NDArray array = manager.arange(10f);
* jshell> NDArrays.where(array.lt(5), array, array.mul(10));
* ND: (10) cpu() float32
* [ 0., 1., 2., 3., 4., 50., 60., 70., 80., 90.]
* jshell> NDArray array = manager.create(new float[]{0f, 1f, 2f, 0f, 2f, 4f, 0f, 3f, 6f}, new Shape(3, 3));
* jshell> NDArrays.where(array.lt(4), array, manager.create(-1f));
* ND: (3, 3) cpu() float32
* [[ 0., 1., 2.],
* [ 0., 2., -1.],
* [ 0., 3., -1.],
* ]
*
*
* @param condition the condition {@code NDArray}
* @param a the first {@link NDArray}
* @param b the other {@link NDArray}
* @return the result {@link NDArray}
*/
public static NDArray where(NDArray condition, NDArray a, NDArray b) {
return a.getNDArrayInternal().where(condition, b);
}
/**
* Returns the maximum of a {@link NDArray} and a number element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {2f, 3f, 4f});
* jshell> NDArrays.maximum(array, 3f);
* ND: (3) cpu() float32
* [3., 3., 4.]
*
*
* @param a the {@link NDArray} to be compared
* @param n the number to be compared
* @return the maximum of a {@link NDArray} and a number element-wise
*/
public static NDArray maximum(NDArray a, Number n) {
return a.maximum(n);
}
/**
* Returns the maximum of a number and a {@link NDArray} element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {2f, 3f, 4f});
* jshell> NDArrays.maximum(3f, array);
* ND: (3) cpu() float32
* [3., 3., 4.]
*
*
* @param n the number to be compared
* @param a the {@link NDArray} to be compared
* @return the maximum of a number and a {@link NDArray} element-wise
*/
public static NDArray maximum(Number n, NDArray a) {
return maximum(a, n);
}
/**
* Returns the maximum of {@link NDArray} a and {@link NDArray} b element-wise.
*
* The shapes of {@link NDArray} a and {@link NDArray} b must be broadcastable.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {2f, 3f, 4f});
* jshell> NDArray array2 = manager.create(new float[] {1f, 5f, 2f});
* jshell> NDArrays.maximum(array1, array2);
* ND: (3) cpu() float32
* [2., 5., 4.]
* jshell> NDArray array1 = manager.eye(2);
* jshell> NDArray array2 = manager.create(new float[] {0.5f, 2f});
* jshell> NDArrays.maximum(array1, array2); // broadcasting
* ND: (2, 2) cpu() float32
* [[1. , 2. ],
* [0.5, 2. ],
* ]
*
*
* @param a the {@link NDArray} to be compared
* @param b the {@link NDArray} to be compared
* @return the maximum of {@link NDArray} a and {@link NDArray} b element-wise
*/
public static NDArray maximum(NDArray a, NDArray b) {
return a.maximum(b);
}
/**
* Returns the minimum of a {@link NDArray} and a number element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {2f, 3f, 4f});
* jshell> NDArrays.minimum(array, 3f);
* ND: (3) cpu() float32
* [2., 3., 3.]
*
*
* @param a the {@link NDArray} to be compared
* @param n the number to be compared
* @return the minimum of a {@link NDArray} and a number element-wise
*/
public static NDArray minimum(NDArray a, Number n) {
return a.minimum(n);
}
/**
* Returns the minimum of a number and a {@link NDArray} element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {2f, 3f, 4f});
* jshell> NDArrays.minimum(3f, array);
* ND: (3) cpu() float32
* [2., 3., 3.]
*
*
* @param n the number to be compared
* @param a the {@link NDArray} to be compared
* @return the minimum of a number and a {@link NDArray} element-wise
*/
public static NDArray minimum(Number n, NDArray a) {
return minimum(a, n);
}
/**
* Returns the minimum of {@link NDArray} a and {@link NDArray} b element-wise.
*
* The shapes of {@link NDArray} a and {@link NDArray} b must be broadcastable.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {2f, 3f, 4f});
* jshell> NDArray array2 = manager.create(new float[] {1f, 5f, 2f});
* jshell> NDArrays.minimum(array1, array2);
* ND: (3) cpu() float32
* [1., 3., 2.]
* jshell> NDArray array1 = manager.eye(2);
* jshell> NDArray array2 = manager.create(new float[] {0.5f, 2f});
* jshell> NDArrays.minimum(array1, array2); // broadcasting
* ND: (2, 2) cpu() float32
* [[0.5, 0. ],
* [0. , 1. ],
* ]
*
*
* @param a the {@link NDArray} to be compared
* @param b the {@link NDArray} to be compared
* @return the minimum of {@link NDArray} a and {@link NDArray} b element-wise
*/
public static NDArray minimum(NDArray a, NDArray b) {
return a.minimum(b);
}
/**
* Returns portion of the {@link NDArray} given the index boolean {@link NDArray} along first
* axis.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f, 3f, 4f, 5f, 6f}, new Shape(3, 2));
* jshell> NDArray mask = manager.create(new boolean[] {true, false, true});
* jshell> NDArrays.booleanMask(array, mask);
* ND: (2, 2) cpu() float32
* [[1., 2.],
* [5., 6.],
* ]
*
*
* @param data the {@link NDArray} to operate on
* @param index the boolean {@link NDArray} mask
* @return the result {@link NDArray}
*/
public static NDArray booleanMask(NDArray data, NDArray index) {
return booleanMask(data, index, 0);
}
/**
* Returns portion of the {@link NDArray} given the index boolean {@link NDArray} along given
* axis.
*
* @param data the {@link NDArray} to operate on
* @param index the boolean {@link NDArray} mask
* @param axis an integer that represents the axis of {@link NDArray} to mask from
* @return the result {@link NDArray}
*/
public static NDArray booleanMask(NDArray data, NDArray index, int axis) {
return data.booleanMask(index, axis);
}
/**
* Sets all elements of the given {@link NDArray} outside the sequence {@link NDArray} to a
* constant value.
*
* This function takes an n-dimensional input array of the form [batch_size,
* max_sequence_length, ....] and returns an array of the same shape. Parameter {@code
* sequenceLength} is used to handle variable-length sequences. {@code sequenceLength} should be
* an input array of positive ints of dimension [batch_size].
*
* @param data the {@link NDArray} to operate on
* @param sequenceLength used to handle variable-length sequences
* @param value the constant value to be set
* @return the result {@link NDArray}
*/
public static NDArray sequenceMask(NDArray data, NDArray sequenceLength, float value) {
return data.sequenceMask(sequenceLength, value);
}
/**
* Sets all elements of the given {@link NDArray} outside the sequence {@link NDArray} to 0.
*
*
This function takes an n-dimensional input array of the form [batch_size,
* max_sequence_length, ....] and returns an array of the same shape. Parameter {@code
* sequenceLength} is used to handle variable-length sequences. {@code sequenceLength} should be
* an input array of positive ints of dimension [batch_size].
*
* @param data the {@link NDArray} to operate on
* @param sequenceLength used to handle variable-length sequences
* @return the result {@link NDArray}
*/
public static NDArray sequenceMask(NDArray data, NDArray sequenceLength) {
return data.sequenceMask(sequenceLength);
}
////////////////////////////////////////
// Operations: Element Arithmetic
////////////////////////////////////////
/**
* Adds a number to the {@link NDArray} element-wise.
*
*
Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.add(array, 2f);
* ND: (2) cpu() float32
* [3., 4.]
*
*
* @param a the {@link NDArray} to be added to
* @param n the number to add
* @return the result {@link NDArray}
*/
public static NDArray add(NDArray a, Number n) {
return a.add(n);
}
/**
* Adds a {@link NDArray} to a number element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.add(2f, array);
* ND: (2) cpu() float32
* [3., 4.]
*
*
* @param n the number to be added to
* @param a the {@link NDArray} to add
* @return the result {@link NDArray}
*/
public static NDArray add(Number n, NDArray a) {
return a.add(n);
}
/**
* Adds a {@link NDArray} to a {@link NDArray} element-wise.
*
* The shapes of all of the {@link NDArray}s must be the same.
*
*
Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.add(array, array, array);
* ND: (2) cpu() float32
* [3., 6.]
*
*
* @param arrays the {@link NDArray}s to add together
* @return the result {@link NDArray}
* @throws IllegalArgumentException arrays must have at least two elements
* @throws IllegalArgumentException the shape of all inputs must be the same
*/
public static NDArray add(NDArray... arrays) {
checkInputs(arrays);
if (arrays.length == 2) {
return arrays[0].add(arrays[1]);
}
try (NDArray array = NDArrays.stack(new NDList(arrays))) {
return array.sum(new int[] {0});
}
}
/**
* Subtracts a number from the {@link NDArray} element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> array.sub(2f);
* ND: (2) cpu() float32
* [-1., 0.]
*
*
* @param a the {@link NDArray} to be subtracted
* @param n the number to subtract from
* @return the result {@link NDArray}
*/
public static NDArray sub(NDArray a, Number n) {
return a.sub(n);
}
/**
* Subtracts a {@link NDArray} from a number element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.sub(3f, array);
* ND: (2) cpu() float32
* [2., 1.]
*
*
* @param n the number to be subtracted
* @param a the {@link NDArray} to subtract from
* @return the result {@link NDArray}
*/
public static NDArray sub(Number n, NDArray a) {
return a.getNDArrayInternal().rsub(n);
}
/**
* Subtracts a {@link NDArray} from a {@link NDArray} element-wise.
*
* The shapes of {@link NDArray} a and {@link NDArray} b must be broadcastable.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.arange(9f).reshape(3, 3);
* jshell> NDArray array2 = manager.arange(3f);
* jshell> NDArrays.sub(array1, array2); // broadcasting
* ND: (3, 3) cpu() float32
* [[0., 0., 0.],
* [3., 3., 3.],
* [6., 6., 6.],
* ]
*
*
* @param a the {@link NDArray} to be subtracted
* @param b the {@link NDArray} to subtract from
* @return the result {@link NDArray}
*/
public static NDArray sub(NDArray a, NDArray b) {
return a.sub(b);
}
/**
* Multiplies the {@link NDArray} by a number element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.mul(array, 3f);
* ND: (2) cpu() float32
* [3., 6.]
*
*
* @param a the NDArray to be multiplied
* @param n the number to multiply by
* @return the result {@link NDArray}
*/
public static NDArray mul(NDArray a, Number n) {
return a.mul(n);
}
/**
* Multiplies a number by a {@link NDArray} element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.mul(3f, array);
* ND: (2) cpu() float32
* [3., 6.]
*
*
* @param n the number to be multiplied
* @param a the {@link NDArray} to multiply by
* @return the result {@link NDArray}
*/
public static NDArray mul(Number n, NDArray a) {
return a.mul(n);
}
/**
* Multiplies all of the {@link NDArray}s together element-wise.
*
* The shapes of all of the {@link NDArray}s must be the same.
*
*
Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.mul(array, array, array);
* ND: (2) cpu() float32
* [1., 8.]
*
*
* @param arrays the {@link NDArray}s to multiply together
* @return the result {@link NDArray}
* @throws IllegalArgumentException arrays must have at least two elements
* @throws IllegalArgumentException the shape of all inputs must be the same
*/
public static NDArray mul(NDArray... arrays) {
checkInputs(arrays);
if (arrays.length == 2) {
return arrays[0].mul(arrays[1]);
}
try (NDArray array = NDArrays.stack(new NDList(arrays))) {
return array.prod(new int[] {0});
}
}
/**
* Divides the {@link NDArray} by a number element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(5f);
* jshell> NDArrays.div(array, 4f);
* ND: (5) cpu() float32
* [0. , 0.25, 0.5 , 0.75, 1. ]
*
*
* @param a the {@link NDArray} to be be divided
* @param n the number to divide by
* @return the result {@link NDArray}
*/
public static NDArray div(NDArray a, Number n) {
return a.div(n);
}
/**
* Divides a number by a {@link NDArray} element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(5f).add(1);
* jshell> NDArrays.div(4f, array);
* ND: (5) cpu() float32
* [4. , 2. , 1.3333, 1. , 0.8 ]
*
*
* @param n the number to be be divided
* @param a the {@link NDArray} to divide by
* @return the result {@link NDArray}
*/
public static NDArray div(Number n, NDArray a) {
return a.getNDArrayInternal().rdiv(n);
}
/**
* Divides a {@link NDArray} by a {@link NDArray} element-wise.
*
* The shapes of {@link NDArray} a and {@link NDArray} b must be broadcastable.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.arange(9f).reshape(3, 3);
* jshell> NDArray array2 = manager.ones(new Shape(3)).mul(10);
* jshell> NDArrays.div(array1, array2); // broadcasting
* ND: (3, 3) cpu() float32
* [[0. , 0.1, 0.2],
* [0.3, 0.4, 0.5],
* [0.6, 0.7, 0.8],
* ]
*
*
* @param a the {@link NDArray} to be be divided
* @param b the {@link NDArray} to divide by
* @return the result {@link NDArray}
*/
public static NDArray div(NDArray a, NDArray b) {
return a.div(b);
}
/**
* Returns element-wise remainder of division.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(7f);
* jshell> NDArrays.mod(array, 5f);
* ND: (7) cpu() float32
* [0., 1., 2., 3., 4., 0., 1.]
*
*
* @param a the dividend {@link NDArray}
* @param n the divisor number
* @return the result {@link NDArray}
*/
public static NDArray mod(NDArray a, Number n) {
return a.mod(n);
}
/**
* Returns element-wise remainder of division.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(7f).add(1);
* jshell> NDArrays.mod(5f, array);
* ND: (7) cpu() float32
* [0., 1., 2., 1., 0., 5., 5.]
*
*
* @param n the dividend number
* @param a the divisor {@link NDArray}
* @return the result {@link NDArray}
*/
public static NDArray mod(Number n, NDArray a) {
return a.getNDArrayInternal().rmod(n);
}
/**
* Returns element-wise remainder of division.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {4f, 7f});
* jshell> NDArray array2 = manager.create(new float[] {2f, 3f});
* jshell> NDArrays.mod(array1, array2);
* ND: (2) cpu() float32
* [0., 1.]
*
*
* @param a the dividend NDArray
* @param b the dividend NDArray
* @return the result {@link NDArray}
*/
public static NDArray mod(NDArray a, NDArray b) {
return a.mod(b);
}
/**
* Takes the power of the {@link NDArray} with a number element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(5f);
* jshell> NDArrays.pow(array, 4f);
* ND: (6) cpu() float32
* [ 0., 1., 8., 27., 64., 125.]
*
*
* @param a the {@link NDArray} to be taken the power with
* @param n the number to take the power with
* @return the result {@link NDArray}
*/
public static NDArray pow(NDArray a, Number n) {
return a.pow(n);
}
/**
* Takes the power of a number with a {@link NDArray} element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(5f);
* jshell> NDArrays.pow(4f, array);
* ND: (5) cpu() float32
* [ 1., 4., 16., 64., 256.]
*
*
* @param n the number to be taken the power with
* @param a the {@link NDArray} to take the power with
* @return the result {@link NDArray}
*/
public static NDArray pow(Number n, NDArray a) {
return a.getNDArrayInternal().rpow(n);
}
/**
* Takes the power of a {@link NDArray} with a {@link NDArray} element-wise.
*
* The shapes of {@link NDArray} a and {@link NDArray} b must be broadcastable.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.arange(6f).reshape(3, 2);
* jshell> NDArray array2 = manager.create(new float[] {2f, 3f});
* jshell> NDArrays.pow(array1, array2); // broadcasting
* ND: (3, 2) cpu() float32
* [[ 0., 1.],
* [ 4., 27.],
* [ 16., 125.],
* ]
*
*
* @param a the {@link NDArray} to be taken the power with
* @param b the {@link NDArray} to take the power with
* @return the result {@link NDArray}
*/
public static NDArray pow(NDArray a, NDArray b) {
return a.pow(b);
}
/**
* Adds a number to the {@link NDArray} element-wise in place.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.addi(array, 2f);
* ND: (2) cpu() float32
* [3., 4.]
* jshell> array;
* ND: (2) cpu() float32
* [3., 4.]
*
*
* @param a the {@link NDArray} to be added to
* @param n the number to add
* @return the result {@link NDArray}
*/
public static NDArray addi(NDArray a, Number n) {
return a.addi(n);
}
/**
* Adds a {@link NDArray} to a number element-wise in place.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.addi(2f, array);
* ND: (2) cpu() float32
* [3., 4.]
* jshell> array;
* ND: (2) cpu() float32
* [3., 4.]
*
*
* @param a the number to be added to
* @param n the {@link NDArray} to add
* @return the result {@link NDArray}
*/
public static NDArray addi(Number n, NDArray a) {
return a.addi(n);
}
/**
* Adds all of the {@link NDArray}s together element-wise in place.
*
* The shapes of all of the {@link NDArray}s must be the same.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {3f, 4f});
* jshell> NDArray array3 = manager.create(new float[] {5f, 6f});
* jshell> NDArrays.addi(array1, array2, array3);
* ND: (2) cpu() float32
* [9., 12.]
* jshell> array;
* ND: (2) cpu() float32
* [9., 12.]
*
*
* @param arrays the {@link NDArray}s to add together
* @return the result {@link NDArray}
* @throws IllegalArgumentException arrays must have at least two elements
*/
public static NDArray addi(NDArray... arrays) {
checkInputs(arrays);
Arrays.stream(arrays).skip(1).forEachOrdered(array -> arrays[0].addi(array));
return arrays[0];
}
/**
* Subtracts a number from the {@link NDArray} element-wise in place.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.subi(array, 2f);
* ND: (2) cpu() float32
* [-1., 0.]
* jshell> array;
* ND: (2) cpu() float32
* [-1., 0.]
*
*
* @param a the {@link NDArray} to be subtracted
* @param n the number to subtract from
* @return the result {@link NDArray}
*/
public static NDArray subi(NDArray a, Number n) {
return a.subi(n);
}
/**
* Subtracts a {@link NDArray} from a number element-wise in place.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.subi(3f, array);
* ND: (2) cpu() float32
* [2., 1.]
* jshell> array;
* ND: (2) cpu() float32
* [2., 1.]
*
*
* @param n the number to be subtracted
* @param a the {@link NDArray} to subtract from
* @return the result {@link NDArray}
*/
public static NDArray subi(Number n, NDArray a) {
return a.getNDArrayInternal().rsubi(n);
}
/**
* Subtracts a {@link NDArray} from a {@link NDArray} element-wise in place.
*
* The shapes of {@link NDArray} a and {@link NDArray} b must be broadcastable.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.arange(9f).reshape(3, 3);
* jshell> NDArray array2 = manager.arange(3f);
* jshell> NDArrays.subi(array1, array2); // broadcasting
* ND: (3, 3) cpu() float32
* [[0., 0., 0.],
* [3., 3., 3.],
* [6., 6., 6.],
* ]
* jshell> array1;
* [[0., 0., 0.],
* [3., 3., 3.],
* [6., 6., 6.],
* ]
*
*
* @param a the {@link NDArray} to be subtracted
* @param b the {@link NDArray} to subtract from
* @return the result {@link NDArray}
*/
public static NDArray subi(NDArray a, NDArray b) {
return a.subi(b);
}
/**
* Multiplies the {@link NDArray} by a number element-wise in place.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.muli(array, 3f);
* ND: (2) cpu() float32
* [3., 6.]
* jshell> array;
* ND: (2) cpu() float32
* [3., 6.]
*
*
* @param a the NDArray to be multiplied
* @param n the number to multiply by
* @return the result {@link NDArray}
*/
public static NDArray muli(NDArray a, Number n) {
return a.muli(n);
}
/**
* Multiplies a number by a {@link NDArray} element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.muli(3f, array);
* ND: (2) cpu() float32
* [3., 6.]
* jshell> array;
* ND: (2) cpu() float32
* [3., 6.]
*
*
* @param n the number to multiply by
* @param a the {@link NDArray} to multiply by
* @return the result {@link NDArray}
*/
public static NDArray muli(Number n, NDArray a) {
return a.muli(n);
}
/**
* Multiplies all of the {@link NDArray}s together element-wise in place.
*
* The shapes of all of the {@link NDArray}s must be the same.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {3f, 4f});
* jshell> NDArray array3 = manager.create(new float[] {5f, 6f});
* jshell> NDArrays.muli(array1, array2, array3);
* ND: (2) cpu() float32
* [15., 48.]
* jshell> array;
* ND: (2) cpu() float32
* [15., 48.]
*
*
* @param arrays the {@link NDArray}s to multiply together
* @return the result {@link NDArray}
* @throws IllegalArgumentException arrays must have at least two elements
*/
public static NDArray muli(NDArray... arrays) {
checkInputs(arrays);
Arrays.stream(arrays).skip(1).forEachOrdered(array -> arrays[0].muli(array));
return arrays[0];
}
/**
* Divides a number by a {@link NDArray} element-wise in place.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(5f);
* jshell> NDArrays.divi(array, 4f);
* ND: (5) cpu() float32
* [0. , 0.25, 0.5 , 0.75, 1. ]
* jshell> array;
* ND: (5) cpu() float32
* [0. , 0.25, 0.5 , 0.75, 1. ]
*
*
* @param a the {@link NDArray} to be be divided
* @param n the number to divide by
* @return the result {@link NDArray}
*/
public static NDArray divi(NDArray a, Number n) {
return a.divi(n);
}
/**
* Divides a number by a {@link NDArray} element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(5f).add(1);
* jshell> NDArrays.divi(4f, array);
* ND: (5) cpu() float32
* [4. , 2. , 1.3333, 1. , 0.8 ]
* jshell> array;
* ND: (5) cpu() float32
* [4. , 2. , 1.3333, 1. , 0.8 ]
*
*
* @param n the number to be be divided
* @param a the {@link NDArray} to divide by
* @return the result {@link NDArray}
*/
public static NDArray divi(Number n, NDArray a) {
return a.getNDArrayInternal().rdivi(n);
}
/**
* Divides a {@link NDArray} by a {@link NDArray} element-wise.
*
* The shapes of {@link NDArray} a and {@link NDArray} b must be broadcastable.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.arange(9f).reshape(3, 3);
* jshell> NDArray array2 = manager.ones(new Shape(3)).mul(10);
* jshell> NDArrays.divi(array1, array2); // broadcasting
* ND: (3, 3) cpu() float32
* [[0. , 0.1, 0.2],
* [0.3, 0.4, 0.5],
* [0.6, 0.7, 0.8],
* ]
* jshell> array1;
* [[0. , 0.1, 0.2],
* [0.3, 0.4, 0.5],
* [0.6, 0.7, 0.8],
* ]
*
*
* @param a the {@link NDArray} to be be divided
* @param b the {@link NDArray} to divide by
* @return the result {@link NDArray}
*/
public static NDArray divi(NDArray a, NDArray b) {
return a.divi(b);
}
/**
* Returns element-wise remainder of division in place.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(7f);
* jshell> NDArrays.modi(array, 5f);
* ND: (7) cpu() float32
* [0., 1., 2., 3., 4., 0., 1.]
* jshell> array;
* ND: (7) cpu() float32
* [0., 1., 2., 3., 4., 0., 1.]
*
*
* @param a the dividend {@link NDArray}
* @param n the divisor number
* @return the result {@link NDArray}
*/
public static NDArray modi(NDArray a, Number n) {
return a.modi(n);
}
/**
* Returns element-wise remainder of division in place.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(7f);
* jshell> NDArrays.modi(5f, array);
* ND: (7) cpu() float32
* [0., 0., 1., 2., 1., 0., 5.]
* jshell> array;
* ND: (7) cpu() float32
* [0., 0., 1., 2., 1., 0., 5.]
*
*
* @param n the dividend number
* @param a the divisor {@link NDArray}
* @return the result {@link NDArray}
*/
public static NDArray modi(Number n, NDArray a) {
return a.getNDArrayInternal().rmodi(n);
}
/**
* Returns element-wise remainder of division.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {4f, 7f});
* jshell> NDArray array2 = manager.create(new float[] {2f, 3f});
* jshell> NDArrays.modi(array1, array2);
* ND: (2) cpu() float32
* [0., 1.]
* jshell> array1;
* ND: (2) cpu() float32
* [0., 1.]
*
*
* @param a the dividend NDArray
* @param b the dividend NDArray
* @return the result {@link NDArray}
*/
public static NDArray modi(NDArray a, NDArray b) {
return a.modi(b);
}
/**
* Takes the power of the {@link NDArray} with a number element-wise in place.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(5f);
* jshell> NDArrays.powi(array, 4f);
* ND: (6) cpu() float32
* [ 0., 1., 8., 27., 64., 125.]
* jshell> array;
* ND: (6) cpu() float32
* [ 0., 1., 8., 27., 64., 125.]
*
*
* @param a the {@link NDArray} to be taken the power with
* @param n the number to take the power with
* @return the result {@link NDArray}
*/
public static NDArray powi(NDArray a, Number n) {
return a.powi(n);
}
/**
* Takes the power of a number with a {@link NDArray} element-wise in place.
*
* Examples
*
*
* jshell> NDArray array = manager.arange(5f);
* jshell> NDArrays.powi(4f, array);
* ND: (5) cpu() float32
* [ 1., 4., 16., 64., 256.]
* jshell> array;
* ND: (5) cpu() float32
* [ 1., 4., 16., 64., 256.]
*
*
* @param n the number to be taken the power with
* @param a the {@link NDArray} to take the power with
* @return the result {@link NDArray}
*/
public static NDArray powi(Number n, NDArray a) {
return a.getNDArrayInternal().rpowi(n);
}
/**
* Takes the power of a {@link NDArray} with a {@link NDArray} element-wise.
*
* The shapes of {@link NDArray} a and {@link NDArray} b must be broadcastable.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.arange(6f).reshape(3, 2);
* jshell> NDArray array2 = manager.create(new float[] {2f, 3f});
* jshell> NDArrays.powi(array1, array2); // broadcasting
* ND: (3, 2) cpu() float32
* [[ 0., 1.],
* [ 4., 27.],
* [ 16., 125.],
* ]
* jshell> array1;
* ND: (3, 2) cpu() float32
* [[ 0., 1.],
* [ 4., 27.],
* [ 16., 125.],
* ]
*
*
* @param a the {@link NDArray} to be taken the power with
* @param b the {@link NDArray} to take the power with
* @return the result {@link NDArray}
*/
public static NDArray powi(NDArray a, NDArray b) {
return a.powi(b);
}
/**
* Dot product of {@link NDArray} a and {@link NDArray} b.
*
*
* - If both the {@link NDArray} and the other {@link NDArray} are 1-D {@link NDArray}s, it
* is inner product of vectors (without complex conjugation).
*
- If both the {@link NDArray} and the other {@link NDArray} are 2-D {@link NDArray}s, it
* is matrix multiplication.
*
- If either the {@link NDArray} or the other {@link NDArray} is 0-D {@link NDArray}
* (scalar), it is equivalent to mul.
*
- If the {@link NDArray} is N-D {@link NDArray} and the other {@link NDArray} is 1-D
* {@link NDArray}, it is a sum product over the last axis of those.
*
- If the {@link NDArray} is N-D {@link NDArray} and the other {@link NDArray} is M-D
* {@link NDArray}(where M>=2), it is a sum product over the last axis of this
* {@link NDArray} and the second-to-last axis of the other {@link NDArray}
*
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {1f, 2f, 3f});
* jshell> NDArray array2 = manager.create(new float[] {4f, 5f, 6f});
* jshell> NDArrays.dot(array1, array2); // inner product
* ND: () cpu() float32
* 32.
* jshell> array1 = manager.create(new float[] {1f, 2f, 3f, 4f}, new Shape(2, 2));
* jshell> array2 = manager.create(new float[] {5f, 6f, 7f, 8f}, new Shape(2, 2));
* jshell> NDArrays.dot(array1, array2); // matrix multiplication
* ND: (2, 2) cpu() float32
* [[19., 22.],
* [43., 50.],
* ]
* jshell> array1 = manager.create(new float[] {1f, 2f, 3f, 4f}, new Shape(2, 2));
* jshell> array2 = manager.create(5f);
* jshell> NDArrays.dot(array1, array2);
* ND: (2, 2) cpu() float32
* [[ 5., 10.],
* [15., 20.],
* ]
* jshell> array1 = manager.create(new float[] {1f, 2f, 3f, 4f}, new Shape(2, 2));
* jshell> array2 = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.dot(array1, array2);
* ND: (2) cpu() float32
* [ 5., 11.]
* jshell> array1 = manager.create(new float[] {1f, 2f, 3f, 4f, 5f, 6f, 7f, 8f}, new Shape(2, 2, 2));
* jshell> array2 = manager.create(new float[] {1f, 2f, 3f ,4f}, new Shape(2, 2));
* jshell> NDArrays.dot(array1, array2);
* ND: (2, 2, 2) cpu() float32
* [[[ 7., 10.],
* [15., 22.],
* ],
* [[23., 34.],
* [31., 46.],
* ],
* ]
*
*
* @param a the {@link NDArray} to perform dot product with
* @param b the {@link NDArray} to perform dot product with
* @return the result {@link NDArray}
*/
public static NDArray dot(NDArray a, NDArray b) {
return a.dot(b);
}
/**
* Product matrix of this {@code NDArray} and the other {@code NDArray}.
*
* The behavior depends on the arguments in the following way.
*
*
* - If both this {@code NDArray} and the other {@code NDArray} are 2-D {@code NDArray}s,
* they are multiplied like conventional matrices
*
- If either this {@code NDArray} or the other {@code NDArray} is N-D {@code NDArray}, N
* > 2 , it is treated as a stack of matrices residing in the last two indexes and
* broadcast accordingly.
*
- If this {@code NDArray} is 1-D {@code NDArray}, it is promoted to a matrix by
* prepending a 1 to its dimensions. After matrix multiplication the prepended 1 is
* removed.
*
- If other {@code NDArray} is 1-D {@code NDArray}, it is promoted to a matrix by
* appending a 1 to its dimensions. After matrix multiplication the appended 1 is removed.
*
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {1f, 0f, 0f, 1f}, new Shape(2, 2));
* jshell> NDArray array2 = manager.create(new float[] {4f, 1f, 2f, 2f}, new Shape(2, 2));
* jshell> NDArrays.matMul(array1, array2); // for 2-D arrays, it is the matrix product
* ND: (2, 2) cpu() float32
* [[4., 1.],
* [2., 2.],
* ]
* jshell> array1 = manager.create(new float[] {1f, 0f, 0f, 1f}, new Shape(2, 2));
* jshell> array2 = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.matMul(array1, array2);
* ND: (2) cpu() float32
* [1., 2.]
* jshell> array1 = manager.create(new float[] {1f, 0f, 0f, 1f}, new Shape(2, 2));
* jshell> array2 = manager.create(new float[] {1f, 2f});
* jshell> NDArrays.matMul(array1, array2);
* ND: (2) cpu() float32
* [1., 2.]
* jshell> array1 = manager.arange(2f * 2f * 4f).reshape(2, 2, 4);
* jshell> array2 = manager.arange(2f * 2f * 4f).reshape(2, 4, 2);
* jshell> NDArrays.matMul(array1, array2);
* ND: () cpu() float32
* 98.
*
*
* @param a the {@link NDArray} to perform matrix product with
* @param b the {@link NDArray} to perform matrix product with
* @return the result {@code NDArray}
*/
public static NDArray matMul(NDArray a, NDArray b) {
return a.matMul(b);
}
/**
* Joins a sequence of {@link NDArray}s in {@link NDList} along the first axis.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {0f, 1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {3f, 4f, 5f});
* jshell> NDArray array3 = manager.create(new float[] {6f, 7f, 8f});
* jshell> NDArrays.stack(new NDList(array1, array2, array3));
* ND: (3, 3) cpu() float32
* [[0., 1., 2.],
* [3., 4., 5.],
* [6., 7., 8.],
* ]
*
*
* @param arrays the input {@link NDList}. Each {@link NDArray} in the {@link NDList} must have
* the same shape as the {@link NDArray}
* @return the result {@link NDArray}. The stacked {@link NDArray} has one more dimension than
* the {@link NDArray}s in {@link NDList}
*/
public static NDArray stack(NDList arrays) {
return stack(arrays, 0);
}
/**
* Joins a sequence of {@link NDArray}s in {@link NDList} along a new axis.
*
* The axis parameter specifies the index of the new axis in the dimensions of the result.
* For example, if axis=0 it will be the first dimension and if axis=-1 it will be the last
* dimension.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {0f, 1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {3f, 4f, 5f});
* jshell> NDArrays.stack(new NDList(array1, array2), 0);
* ND: (2, 3) cpu() float32
* [[0., 1., 2.],
* [3., 4., 5.],
* ]
* jshell> NDArray array1 = manager.create(new float[] {0f, 1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {3f, 4f, 5f});
* jshell> NDArrays.stack(new NDList(array1, array2), 1);
* ND: (3, 2) cpu() float32
* [[0., 3.],
* [1., 4.],
* [2., 5.],
* ]
*
*
* @param arrays the input {@link NDList}. Each {@link NDArray} in the {@link NDList} must have
* the same shape as the {@link NDArray}
* @param axis the axis in the result {@link NDArray} along which the input {@link NDList} are
* stacked
* @return the result {@link NDArray}. The stacked {@link NDArray} has one more dimension than
* the the {@link NDArray}
*/
public static NDArray stack(NDList arrays, int axis) {
NDArray array = arrays.head();
return array.getNDArrayInternal().stack(arrays.subNDList(1), axis);
}
/**
* Joins a {@link NDList} along the first axis.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {0f, 1f, 2f});
* jshell> NDArray array2 = manager.create(new float[] {3f, 4f, 5f});
* jshell> NDArray array3 = manager.create(new float[] {6f, 7f, 8f});
* jshell> NDArrays.concat(new NDList(array1, array2, array3));
* ND: (9) cpu() float32
* [0., 1., 2., 3., 4., 5., 6., 7., 8.]
*
*
* @param arrays a {@link NDList} which have the same shape as the {@link NDArray}, except in
* the dimension corresponding to axis
* @return the concatenated {@link NDArray}
*/
public static NDArray concat(NDList arrays) {
return concat(arrays, 0);
}
/**
* Joins a {@link NDList} along an existing axis.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new float[] {1f, 2f, 3f, 4f}, new Shape(2, 2));
* jshell> NDArray array2 = manager.create(new float[] {5f, 6f}, new Shape(1, 2));
* jshell> NDArrays.concat(new NDList(array1, array2), 0);
* ND: (3, 2) cpu() float32
* [[1., 2.],
* [3., 4.],
* [5., 6.],
* ]
* jshell> NDArrays.concat(new NDList(array1, array2.transpose()), 1);
* ND: (2, 3) cpu() float32
* [[1., 2., 5.],
* [3., 4., 6.],
* ]
*
*
* @param arrays a {@link NDList} which have the same shape as the {@link NDArray}, except in
* the dimension corresponding to axis
* @param axis the axis along which the {@link NDList} will be joined
* @return the concatenated {@link NDArray}
*/
public static NDArray concat(NDList arrays, int axis) {
NDArray array = arrays.head();
return array.getNDArrayInternal().concat(arrays.subNDList(1), axis);
}
/**
* Returns the truth value of {@link NDArray} a AND {@link NDArray} b element-wise.
*
* The shapes of {@link NDArray} a and {@link NDArray} b must be broadcastable.
*
*
Examples
*
*
* jshell> NDArray array1 = manager.create(new boolean[] {true});
* jshell> NDArray array2 = manager.create(new boolean[] {false});
* jshell> NDArrays.logicalAnd(array1, array2);
* ND: (1) cpu() boolean
* [false]
* jshell> array1 = manager.create(new boolean[] {true, false});
* jshell> array2 = manager.create(new boolean[] {false, false});
* jshell> NDArrays.logicalAnd(array.gt(1), array.lt(4));
* ND: (2) cpu() boolean
* [false, false]
*
*
* @param a the {@link NDArray} to operate on
* @param b the {@link NDArray} to operate on
* @return the boolean {@link NDArray} of the logical AND operation applied to the elements of
* the {@link NDArray} a and {@link NDArray} b
*/
public static NDArray logicalAnd(NDArray a, NDArray b) {
return a.logicalAnd(b);
}
/**
* Computes the truth value of {@link NDArray} a AND {@link NDArray} b element-wise.
*
* Examples
*
*
* jshell> NDArray array1 = manager.create(new boolean[] {true});
* jshell> NDArray array2 = manager.create(new boolean[] {false});
* jshell> NDArrays.logicalOr(array1, array2);
* ND: (1) cpu() boolean
* [ true]
* jshell> array1 = manager.create(new boolean[] {true, false});
* jshell> array2 = manager.create(new boolean[] {false, false});
* jshell> NDArrays.logicalOr(array1, array2);
* ND: (2) cpu() boolean
* [ true, false]
*
*
*
* jshell> NDArray array = manager.arange(5f);
* jshell> NDArrays.logicalOr(array.lt(1), array.gt(3));
* ND: (5) cpu() boolean
* [ true, false, false, false, true]
*
*
* @param a the {@link NDArray} to operate on
* @param b the {@link NDArray} to operate on
* @return the boolean {@link NDArray} of the logical AND operation applied to the elements of
* the {@link NDArray} a and {@link NDArray} b
*/
public static NDArray logicalOr(NDArray a, NDArray b) {
return a.logicalOr(b);
}
/**
* Computes the truth value of {@link NDArray} a AND {@link NDArray} b element-wise.
*
* Examples
*
*
* jshell> NDArray array = manager.create(new boolean[] {true});
* jshell> NDArrays.logicalXor(array1, array2);
* ND: (1) cpu() boolean
* [ true]
* jshell> array1 = manager.create(new boolean[] {true, false});
* jshell> array2 = manager.create(new boolean[] {false, false});
* jshell> NDArrays.logicalXor(array1, array2);
* ND: (2) cpu() boolean
* [ true, false]
*
*
*
* jshell> NDArray array = manager.arange(5f);
* jshell> NDArrays.logicalXor(array.lt(1), array.gt(3));
* ND: (5) cpu() boolean
* [ true, false, false, false, true]
*
*
* @param a the {@link NDArray} to operate on
* @param b the {@link NDArray} to operate on
* @return the boolean {@link NDArray} of the logical XOR operation applied to the elements of
* the {@link NDArray} a and {@link NDArray} b
*/
public static NDArray logicalXor(NDArray a, NDArray b) {
return a.logicalXor(b);
}
}
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