E5C4 Added the TensorCreation.java example by zaleslaw · Pull Request #7 · tensorflow/java-models · GitHub
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Merged
karllessard merged 2 commits into from
May 19, 2020
Merged

Added the TensorCreation.java example #7

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fd33af9
Added the TensorCreation.java example
zaleslaw May 17, 2020
2ebfa96
Fixed review comments
zaleslaw May 19, 2020
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100 changes: 100 additions & 0 deletions tensorflow-examples/src/main/java/org/tensorflow/model/examples/tensors/TensorCreation.java
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/*
* Copyright 2020 The TensorFlow Authors. 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.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =======================================================================
*/
package org.tensorflow.model.examples.tensors;

import org.tensorflow.Tensor;
import org.tensorflow.tools.Shape;
import org.tensorflow.tools.ndarray.IntNdArray;
import org.tensorflow.tools.ndarray.NdArrays;
import org.tensorflow.types.TInt32;

import java.util.Arrays;

/**
* Creates a few tensors of ranks: 0, 1, 2, 3.
*/
public class TensorCreation {
public static void main(String[] args) {
// Rank 0 Tensor
Tensor<TInt32> rank0Tensor = TInt32.scalarOf(42);

System.out.println("---- Scalar tensor ---------");

System.out.println("DataType: " + rank0Tensor.dataType().name());

System.out.println("Rank: " + rank0Tensor.shape().size());

System.out.println("Shape: " + Arrays.toString(rank0Tensor.shape().asArray()));

rank0Tensor.data().scalars().forEach(value -> System.out.println("Value: " + value.getObject()));

// Rank 1 Tensor
Tensor<TInt32> rank1Tensor = TInt32.vectorOf(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);

System.out.println("---- Vector tensor ---------");

System.out.println("DataType: " + rank1Tensor.dataType().name());

System.out.println("Rank: " + rank1Tensor.shape().size());

System.out.println("Shape: " + Arrays.toString(rank1Tensor.shape().asArray()));

System.out.println("6th element: " + rank1Tensor.data().getInt(5));

// Rank 2 Tensor
// 3x2 matrix of ints.
IntNdArray matrix2d = NdArrays.ofInts(Shape.of(3, 2));

matrix2d.set(NdArrays.vectorOf(1, 2), 0)
.set(NdArrays.vectorOf(3, 4), 1)
.set(NdArrays.vectorOf(5, 6), 2);

Tensor<TInt32> rank2Tensor = TInt32.tensorOf(matrix2d);

System.out.println("---- Matrix tensor ---------");

System.out.println("DataType: " + rank2Tensor.dataType().name());

System.out.println("Rank: " + rank2Tensor.shape().size());

System.out.println("Shape: " + Arrays.toString(rank2Tensor.shape().asArray()));

System.out.println("6th element: " + rank2Tensor.data().getInt(2, 1));

// Rank 3 Tensor
// 3*2*4 matrix of ints.
IntNdArray matrix3d = NdArrays.ofInts(Shape.of(3, 2, 4));

matrix3d.elements(0).forEach(matrix -> {
matrix
.set(NdArrays.vectorOf(1, 2, 3, 4), 0)
.set(NdArrays.vectorOf(5, 6, 7, 8), 1);
});

Tensor<TInt32> rank3Tensor = TInt32.tensorOf(matrix3d);

System.out.println("---- Matrix tensor ---------");

System.out.println("DataType: " + rank3Tensor.dataType().name());

System.out.println("Rank: " + rank3Tensor.shape().size());

System.out.println("Shape: " + Arrays.toString(rank3Tensor.shape().asArray()));

System.out.println("n-th element: " + rank3Tensor.data().getInt(2, 1, 3));
}
}
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