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Merge pull request #1011 from BalashovK/master
Added: complex, real, imag, angle
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,202 @@ | ||
| using Microsoft.VisualStudio.TestTools.UnitTesting; | ||
| using Tensorflow.NumPy; | ||
| using System; | ||
| using System.Collections.Generic; | ||
| using System.Linq; | ||
| using Tensorflow; | ||
| using static Tensorflow.Binding; | ||
| using Buffer = Tensorflow.Buffer; | ||
| using TensorFlowNET.Keras.UnitTest; | ||
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| namespace TensorFlowNET.UnitTest.Basics | ||
| { | ||
| [TestClass] | ||
| public class ComplexTest : EagerModeTestBase | ||
| { | ||
| // Tests for Complex128 | ||
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| [TestMethod] | ||
| public void complex128_basic() | ||
| { | ||
| double[] d_real = new double[] { 1.0, 2.0, 3.0, 4.0 }; | ||
| double[] d_imag = new double[] { -1.0, -3.0, 5.0, 7.0 }; | ||
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| Tensor t_real = tf.constant(d_real, dtype:TF_DataType.TF_DOUBLE); | ||
| Tensor t_imag = tf.constant(d_imag, dtype: TF_DataType.TF_DOUBLE); | ||
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| Tensor t_complex = tf.complex(t_real, t_imag); | ||
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| Tensor t_real_result = tf.math.real(t_complex); | ||
| Tensor t_imag_result = tf.math.imag(t_complex); | ||
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| NDArray n_real_result = t_real_result.numpy(); | ||
| NDArray n_imag_result = t_imag_result.numpy(); | ||
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| double[] d_real_result =n_real_result.ToArray<double>(); | ||
| double[] d_imag_result = n_imag_result.ToArray<double>(); | ||
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| Assert.IsTrue(base.Equal(d_real_result, d_real)); | ||
| Assert.IsTrue(base.Equal(d_imag_result, d_imag)); | ||
| } | ||
| [TestMethod] | ||
| public void complex128_abs() | ||
| { | ||
| tf.enable_eager_execution(); | ||
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| double[] d_real = new double[] { -3.0, -5.0, 8.0, 7.0 }; | ||
| double[] d_imag = new double[] { -4.0, 12.0, -15.0, 24.0 }; | ||
|
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| double[] d_abs = new double[] { 5.0, 13.0, 17.0, 25.0 }; | ||
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| Tensor t_real = tf.constant(d_real, dtype: TF_DataType.TF_DOUBLE); | ||
| Tensor t_imag = tf.constant(d_imag, dtype: TF_DataType.TF_DOUBLE); | ||
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| Tensor t_complex = tf.complex(t_real, t_imag); | ||
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| Tensor t_abs_result = tf.abs(t_complex); | ||
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| double[] d_abs_result = t_abs_result.numpy().ToArray<double>(); | ||
| Assert.IsTrue(base.Equal(d_abs_result, d_abs)); | ||
| } | ||
| [TestMethod] | ||
| public void complex128_conj() | ||
| { | ||
| double[] d_real = new double[] { -3.0, -5.0, 8.0, 7.0 }; | ||
| double[] d_imag = new double[] { -4.0, 12.0, -15.0, 24.0 }; | ||
|
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| double[] d_real_expected = new double[] { -3.0, -5.0, 8.0, 7.0 }; | ||
| double[] d_imag_expected = new double[] { 4.0, -12.0, 15.0, -24.0 }; | ||
|
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| Tensor t_real = tf.constant(d_real, dtype: TF_DataType.TF_DOUBLE); | ||
| Tensor t_imag = tf.constant(d_imag, dtype: TF_DataType.TF_DOUBLE); | ||
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| Tensor t_complex = tf.complex(t_real, t_imag, TF_DataType.TF_COMPLEX128); | ||
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| Tensor t_result = tf.math.conj(t_complex); | ||
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| NDArray n_real_result = tf.math.real(t_result).numpy(); | ||
| NDArray n_imag_result = tf.math.imag(t_result).numpy(); | ||
|
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| double[] d_real_result = n_real_result.ToArray<double>(); | ||
| double[] d_imag_result = n_imag_result.ToArray<double>(); | ||
|
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| Assert.IsTrue(base.Equal(d_real_result, d_real_expected)); | ||
| Assert.IsTrue(base.Equal(d_imag_result, d_imag_expected)); | ||
| } | ||
| [TestMethod] | ||
| public void complex128_angle() | ||
| { | ||
| double[] d_real = new double[] { 0.0, 1.0, -1.0, 0.0 }; | ||
| double[] d_imag = new double[] { 1.0, 0.0, -2.0, -3.0 }; | ||
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| double[] d_expected = new double[] { 1.5707963267948966, 0, -2.0344439357957027, -1.5707963267948966 }; | ||
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| Tensor t_real = tf.constant(d_real, dtype: TF_DataType.TF_DOUBLE); | ||
| Tensor t_imag = tf.constant(d_imag, dtype: TF_DataType.TF_DOUBLE); | ||
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| Tensor t_complex = tf.complex(t_real, t_imag, TF_DataType.TF_COMPLEX128); | ||
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| Tensor t_result = tf.math.angle(t_complex); | ||
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| NDArray n_result = t_result.numpy(); | ||
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| double[] d_result = n_result.ToArray<double>(); | ||
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| Assert.IsTrue(base.Equal(d_result, d_expected)); | ||
| } | ||
|
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| // Tests for Complex64 | ||
| [TestMethod] | ||
| public void complex64_basic() | ||
| { | ||
| tf.init_scope(); | ||
| float[] d_real = new float[] { 1.0f, 2.0f, 3.0f, 4.0f }; | ||
| float[] d_imag = new float[] { -1.0f, -3.0f, 5.0f, 7.0f }; | ||
|
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| Tensor t_real = tf.constant(d_real, dtype: TF_DataType.TF_FLOAT); | ||
| Tensor t_imag = tf.constant(d_imag, dtype: TF_DataType.TF_FLOAT); | ||
|
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| Tensor t_complex = tf.complex(t_real, t_imag); | ||
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| Tensor t_real_result = tf.math.real(t_complex); | ||
| Tensor t_imag_result = tf.math.imag(t_complex); | ||
|
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| // Convert the EagerTensors to NumPy arrays directly | ||
| float[] d_real_result = t_real_result.numpy().ToArray<float>(); | ||
| float[] d_imag_result = t_imag_result.numpy().ToArray<float>(); | ||
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| Assert.IsTrue(base.Equal(d_real_result, d_real)); | ||
| Assert.IsTrue(base.Equal(d_imag_result, d_imag)); | ||
| } | ||
| [TestMethod] | ||
| public void complex64_abs() | ||
| { | ||
| tf.enable_eager_execution(); | ||
|
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| float[] d_real = new float[] { -3.0f, -5.0f, 8.0f, 7.0f }; | ||
| float[] d_imag = new float[] { -4.0f, 12.0f, -15.0f, 24.0f }; | ||
|
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| float[] d_abs = new float[] { 5.0f, 13.0f, 17.0f, 25.0f }; | ||
|
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| Tensor t_real = tf.constant(d_real, dtype: TF_DataType.TF_FLOAT); | ||
| Tensor t_imag = tf.constant(d_imag, dtype: TF_DataType.TF_FLOAT); | ||
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| Tensor t_complex = tf.complex(t_real, t_imag, TF_DataType.TF_COMPLEX64); | ||
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| Tensor t_abs_result = tf.abs(t_complex); | ||
|
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| NDArray n_abs_result = t_abs_result.numpy(); | ||
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| float[] d_abs_result = n_abs_result.ToArray<float>(); | ||
| Assert.IsTrue(base.Equal(d_abs_result, d_abs)); | ||
|
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| } | ||
| [TestMethod] | ||
| public void complex64_conj() | ||
| { | ||
| float[] d_real = new float[] { -3.0f, -5.0f, 8.0f, 7.0f }; | ||
| float[] d_imag = new float[] { -4.0f, 12.0f, -15.0f, 24.0f }; | ||
|
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||
| float[] d_real_expected = new float[] { -3.0f, -5.0f, 8.0f, 7.0f }; | ||
| float[] d_imag_expected = new float[] { 4.0f, -12.0f, 15.0f, -24.0f }; | ||
|
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| Tensor t_real = tf.constant(d_real, dtype: TF_DataType.TF_FLOAT); | ||
| Tensor t_imag = tf.constant(d_imag, dtype: TF_DataType.TF_FLOAT); | ||
|
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| Tensor t_complex = tf.complex(t_real, t_imag, TF_DataType.TF_COMPLEX64); | ||
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| Tensor t_result = tf.math.conj(t_complex); | ||
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| NDArray n_real_result = tf.math.real(t_result).numpy(); | ||
| NDArray n_imag_result = tf.math.imag(t_result).numpy(); | ||
|
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| float[] d_real_result = n_real_result.ToArray<float>(); | ||
| float[] d_imag_result = n_imag_result.ToArray<float>(); | ||
|
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| Assert.IsTrue(base.Equal(d_real_result, d_real_expected)); | ||
| Assert.IsTrue(base.Equal(d_imag_result, d_imag_expected)); | ||
|
|
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| } | ||
| [TestMethod] | ||
| public void complex64_angle() | ||
| { | ||
| float[] d_real = new float[] { 0.0f, 1.0f, -1.0f, 0.0f }; | ||
| float[] d_imag = new float[] { 1.0f, 0.0f, -2.0f, -3.0f }; | ||
|
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| float[] d_expected = new float[] { 1.5707964f, 0f, -2.0344439f, -1.5707964f }; | ||
|
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| Tensor t_real = tf.constant(d_real, dtype: TF_DataType.TF_FLOAT); | ||
| Tensor t_imag = tf.constant(d_imag, dtype: TF_DataType.TF_FLOAT); | ||
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| Tensor t_complex = tf.complex(t_real, t_imag, TF_DataType.TF_COMPLEX64); | ||
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| Tensor t_result = tf.math.angle(t_complex); | ||
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| NDArray n_result = t_result.numpy(); | ||
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| float[] d_result = n_result.ToArray<float>(); | ||
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| Assert.IsTrue(base.Equal(d_result, d_expected)); | ||
| } | ||
| } | ||
| } |
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