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// Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package com.yahoo.tensor;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.fail;
public class TensorParserTestCase {
@Test
public void testSparseParsing() {
assertEquals(Tensor.Builder.of(TensorType.fromSpec("tensor()")).build(),
Tensor.from("{}"));
assertEquals(Tensor.Builder.of(TensorType.fromSpec("tensor(x{})")).cell(1.0, 0).build(),
Tensor.from("{{x:0}:1.0}"));
assertEquals(Tensor.Builder.of(TensorType.fromSpec("tensor(x{})")).cell().label("x", "l0").value(1.0).build(),
Tensor.from("{{x:l0}:1.0}"));
assertEquals("If the type is specified, a dense tensor can be created from the sparse text form",
Tensor.Builder.of(TensorType.fromSpec("tensor(x[1])")).cell(1.0, 0).build(),
Tensor.from("tensor(x[1]):{{x:0}:1.0}"));
}
@Test
public void testDenseParsing() {
assertDense(Tensor.Builder.of(TensorType.fromSpec("tensor()")).build(),
"tensor():{0.0}");
assertDense(Tensor.Builder.of(TensorType.fromSpec("tensor()")).cell(1.3).build(),
"tensor():{1.3}");
assertDense(Tensor.Builder.of(TensorType.fromSpec("tensor(x[])")).cell(1.0, 0).build(),
"tensor(x[]):{{x:0}:1.0}");
assertDense(Tensor.Builder.of(TensorType.fromSpec("tensor(x[1])")).cell(1.0, 0).build(),
"tensor(x[1]):[1.0]");
assertDense(Tensor.Builder.of(TensorType.fromSpec("tensor(x[2])")).cell(1.0, 0).cell(2.0, 1).build(),
"tensor(x[2]):[1.0, 2.0]");
assertDense(Tensor.Builder.of(TensorType.fromSpec("tensor(x[2],y[3])"))
.cell(1.0, 0, 0)
.cell(2.0, 0, 1)
.cell(3.0, 0, 2)
.cell(4.0, 1, 0)
.cell(5.0, 1, 1)
.cell(6.0, 1, 2).build(),
"tensor(x[2],y[3]):[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]");
assertDense(Tensor.Builder.of(TensorType.fromSpec("tensor(x[1],y[2],z[3])"))
.cell(1.0, 0, 0, 0)
.cell(2.0, 0, 0, 1)
.cell(3.0, 0, 0, 2)
.cell(4.0, 0, 1, 0)
.cell(5.0, 0, 1, 1)
.cell(6.0, 0, 1, 2).build(),
"tensor(x[1],y[2],z[3]):[[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]]");
assertDense(Tensor.Builder.of(TensorType.fromSpec("tensor(x[3],y[2],z[1])"))
.cell(1.0, 0, 0, 0)
.cell(2.0, 0, 1, 0)
.cell(3.0, 1, 0, 0)
.cell(4.0, 1, 1, 0)
.cell(5.0, 2, 0, 0)
.cell(6.0, 2, 1, 0).build(),
"tensor(x[3],y[2],z[1]):[[[1.0], [2.0]], [[3.0], [4.0]], [[5.0], [6.0]]]");
assertEquals("Messy input",
Tensor.Builder.of(TensorType.fromSpec("tensor(x[3],y[2],z[1])"))
.cell( 1.0, 0, 0, 0)
.cell( 2.0, 0, 1, 0)
.cell( 3.0, 1, 0, 0)
.cell( 4.0, 1, 1, 0)
.cell( 5.0, 2, 0, 0)
.cell(-6.0, 2, 1, 0).build(),
Tensor.from("tensor( x[3],y[2],z[1]) : [ [ [1.0, 2.0, 3.0] , [4.0, 5,-6.0] ] ]"));
assertEquals("Skipping syntactic sugar",
Tensor.Builder.of(TensorType.fromSpec("tensor(x[3],y[2],z[1])"))
.cell( 1.0, 0, 0, 0)
.cell( 2.0, 0, 1, 0)
.cell( 3.0, 1, 0, 0)
.cell( 4.0, 1, 1, 0)
.cell( 5.0, 2, 0, 0)
.cell(-6.0, 2, 1, 0).build(),
Tensor.from("tensor( x[3],y[2],z[1]) : [1.0, 2.0, 3.0 , 4.0, 5, -6.0]"));
}
private void assertDense(Tensor expectedTensor, String denseFormat) {
assertEquals(denseFormat, expectedTensor, Tensor.from(denseFormat));
assertEquals(denseFormat, expectedTensor.toString());
}
@Test
public void testIllegalStrings() {
assertIllegal("label must be an identifier or integer, not '\"l0\"'",
"{{x:\"l0\"}:1.0}");
assertIllegal("dimension must be an identifier or integer, not ''x''",
"{{'x':\"l0\"}:1.0}");
assertIllegal("dimension must be an identifier or integer, not '\"x\"'",
"{{\"x\":\"l0\", \"y\":\"l0\"}:1.0, {\"x\":\"l0\", \"y\":\"l1\"}:2.0}");
assertIllegal("At {x:0}: '1-.0' is not a valid double",
"{{x:0}:1-.0}");
assertIllegal("At index 0: '1-.0' is not a valid double",
"tensor(x[1]):[1-.0]");
}
private void assertIllegal(String message, String tensor) {
try {
Tensor.from(tensor);
fail("Expected an IllegalArgumentException when parsing " + tensor);
}
catch (IllegalArgumentException e) {
assertEquals(message, e.getMessage());
}
}
}
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