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/* Copyright 2016 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.op.core;
import static org.junit.Assert.assertArrayEquals;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;
import java.io.ByteArrayOutputStream;
import java.io.DataOutputStream;
import java.io.IOException;
import java.nio.ByteBuffer;
import java.nio.DoubleBuffer;
import java.nio.FloatBuffer;
import java.nio.IntBuffer;
import java.nio.LongBuffer;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.junit.runners.JUnit4;
import org.tensorflow.Graph;
import org.tensorflow.Session;
import org.tensorflow.Shape;
import org.tensorflow.Tensor;
import org.tensorflow.op.Scope;
@RunWith(JUnit4.class)
public class ConstantTest {
private static final float EPSILON = 1e-7f;
@Test
public void createInt() {
int value = 1;
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<Integer> op = Constant.create(scope, value);
Tensor<Integer> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(Integer.class);
assertEquals(value, result.intValue());
}
}
@Test
public void createIntBuffer() {
int[] ints = {1, 2, 3, 4};
Shape shape = Shape.make(4);
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<Integer> op = Constant.create(scope, shape, IntBuffer.wrap(ints));
Tensor<Integer> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(Integer.class);
int[] actual = new int[ints.length];
assertArrayEquals(ints, result.copyTo(actual));
}
}
@Test
public void createFloat() {
float value = 1;
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<Float> op = Constant.create(scope, value);
Tensor<Float> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(Float.class);
assertEquals(value, result.floatValue(), 0.0f);
}
}
@Test
public void createFloatBuffer() {
float[] floats = {1, 2, 3, 4};
Shape shape = Shape.make(4);
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<Float> op = Constant.create(scope, shape, FloatBuffer.wrap(floats));
Tensor<Float> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(Float.class);
float[] actual = new float[floats.length];
assertArrayEquals(floats, result.copyTo(actual), EPSILON);
}
}
@Test
public void createDouble() {
double value = 1;
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<Double> op = Constant.create(scope, value);
Tensor<Double> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(Double.class);
assertEquals(value, result.doubleValue(), 0.0);
}
}
@Test
public void createDoubleBuffer() {
double[] doubles = {1, 2, 3, 4};
Shape shape = Shape.make(4);
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<Double> op = Constant.create(scope, shape, DoubleBuffer.wrap(doubles));
Tensor<Double> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(Double.class);
double[] actual = new double[doubles.length];
assertArrayEquals(doubles, result.copyTo(actual), EPSILON);
}
}
@Test
public void createLong() {
long value = 1;
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<Long> op = Constant.create(scope, value);
Tensor<Long> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(Long.class);
assertEquals(value, result.longValue());
}
}
@Test
public void createLongBuffer() {
long[] longs = {1, 2, 3, 4};
Shape shape = Shape.make(4);
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<Long> op = Constant.create(scope, shape, LongBuffer.wrap(longs));
Tensor<Long> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(Long.class);
long[] actual = new long[longs.length];
assertArrayEquals(longs, result.copyTo(actual));
}
}
@Test
public void createBoolean() {
boolean value = true;
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<Boolean> op = Constant.create(scope, value);
Tensor<Boolean> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(Boolean.class);
assertEquals(value, result.booleanValue());
}
}
@Test
public void createStringBuffer() throws IOException {
byte[] data = {(byte) 1, (byte) 2, (byte) 3, (byte) 4};
Shape shape = Shape.unknown();
// byte arrays (DataType.STRING in Tensorflow) are encoded as an offset in the data buffer,
// followed by a varint encoded size, followed by the data.
ByteArrayOutputStream baout = new ByteArrayOutputStream();
DataOutputStream out = new DataOutputStream(baout);
// Offset in array.
out.writeLong(0L);
// Varint encoded length of buffer.
// For any number < 0x80, the varint encoding is simply the number itself.
// https://developers.google.com/protocol-buffers/docs/encoding#varints
assertTrue(data.length < 0x80);
out.write(data.length);
out.write(data);
out.close();
byte[] content = baout.toByteArray();
try (Graph g = new Graph();
Session sess = new Session(g)) {
Scope scope = new Scope(g);
Constant<String> op = Constant.create(scope, String.class, shape, ByteBuffer.wrap(content));
Tensor<String> result = sess.runner().fetch(op.asOutput()).run().get(0).expect(String.class);
assertArrayEquals(data, result.bytesValue());
}
}
}
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