From 481579e6149f500632e051d98cf5d23f97ff67ea Mon Sep 17 00:00:00 2001
From: carlosuc3m <100329787@alumnos.uc3m.es>
Date: Tue, 12 Jul 2022 18:45:45 +0200
Subject: [PATCH] Merge branch 'develop' of
https://gitlab.pasteur.fr/bia/tensorflow-1-interface.git into develop
---
.../tensorflow/v1/tensor/ImgLib2Builder.java | 132 ++++++++++++++++++
.../tensorflow/v1/tensor/TensorBuilder.java | 9 +-
2 files changed, 137 insertions(+), 4 deletions(-)
create mode 100644 src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/ImgLib2Builder.java
diff --git a/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/ImgLib2Builder.java b/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/ImgLib2Builder.java
new file mode 100644
index 0000000..146cc67
--- /dev/null
+++ b/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/ImgLib2Builder.java
@@ -0,0 +1,132 @@
+package org.bioimageanalysis.icy.tensorflow.v1.tensor;
+
+import java.nio.ByteBuffer;
+import java.nio.DoubleBuffer;
+import java.nio.FloatBuffer;
+import java.nio.IntBuffer;
+
+import org.nd4j.linalg.api.buffer.DataType;
+import org.nd4j.linalg.api.ndarray.INDArray;
+import org.nd4j.linalg.factory.Nd4j;
+import org.tensorflow.Tensor;
+import org.tensorflow.types.UInt8;
+
+/**
+ * A {@link INDArray} builder for TensorFlow {@link Tensor} objects.
+ *
+ * @author Carlos Garcia Lopez de Haro
+ */
+public final class ImgLib2Builder
+{
+
+ /**
+ * Not used (Utility class).
+ */
+ private ImgLib2Builder()
+ {
+ }
+
+ /**
+ * Creates a {@link INDArray} from a given {@link Tensor} and an array with its dimensions order.
+ *
+ * @param tensor
+ * The tensor data is read from.
+ * @return The INDArray built from the tensor.
+ * @throws IllegalArgumentException
+ * If the tensor type is not supported.
+ */
+ @SuppressWarnings("unchecked")
+ public static INDArray build(Tensor<?> tensor) throws IllegalArgumentException
+ {
+ // Create an INDArray of the same type of the tensor
+ switch (tensor.dataType())
+ {
+ case UINT8:
+ return buildFromTensorByte((Tensor<UInt8>) tensor);
+ case INT32:
+ return buildFromTensorInt((Tensor<Integer>) tensor);
+ case FLOAT:
+ return buildFromTensorFloat((Tensor<Float>) tensor);
+ case DOUBLE:
+ return buildFromTensorDouble((Tensor<Double>) tensor);
+ default:
+ throw new IllegalArgumentException("Unsupported tensor type: " + tensor.dataType());
+ }
+ }
+
+ /**
+ * Builds a {@link INDArray} from a unsigned byte-typed {@link Tensor}.
+ *
+ * @param tensor
+ * The tensor data is read from.
+ * @return The INDArray built from the tensor of type {@link DataType#UBYTE}.
+ */
+ private static INDArray buildFromTensorByte(Tensor<UInt8> tensor)
+ {
+ long[] tensorShape = tensor.shape();
+ int totalSize = 1;
+ for (long i : tensorShape) {totalSize *= i;}
+ byte[] flatImageArray = new byte[totalSize];
+ ByteBuffer outBuff = ByteBuffer.wrap(flatImageArray);
+ tensor.writeTo(outBuff);
+ outBuff = null;
+ return Nd4j.create(flatImageArray, tensorShape, DataType.INT8);
+ }
+
+ /**
+ * Builds a {@link INDArray} from a unsigned integer-typed {@link Tensor}.
+ *
+ * @param tensor
+ * The tensor data is read from.
+ * @return The sequence built from the tensor of type {@link DataType#INT}.
+ */
+ private static INDArray buildFromTensorInt(Tensor<Integer> tensor)
+ {
+ long[] tensorShape = tensor.shape();
+ int totalSize = 1;
+ for (long i : tensorShape) {totalSize *= i;}
+ int[] flatImageArray = new int[totalSize];
+ IntBuffer outBuff = IntBuffer.wrap(flatImageArray);
+ tensor.writeTo(outBuff);
+ outBuff = null;
+ return Nd4j.create(flatImageArray, tensorShape, DataType.INT32);
+ }
+
+ /**
+ * Builds a {@link INDArray} from a unsigned float-typed {@link Tensor}.
+ *
+ * @param tensor
+ * The tensor data is read from.
+ * @return The INDArray built from the tensor of type {@link DataType#FLOAT}.
+ */
+ private static INDArray buildFromTensorFloat(Tensor<Float> tensor)
+ {
+ long[] tensorShape = tensor.shape();
+ int totalSize = 1;
+ for (long i : tensorShape) {totalSize *= i;}
+ float[] flatImageArray = new float[totalSize];
+ FloatBuffer outBuff = FloatBuffer.wrap(flatImageArray);
+ tensor.writeTo(outBuff);
+ outBuff = null;
+ return Nd4j.create(flatImageArray, tensorShape, DataType.FLOAT);
+ }
+
+ /**
+ * Builds a {@link INDArray} from a unsigned double-typed {@link Tensor}.
+ *
+ * @param tensor
+ * The tensor data is read from.
+ * @return The INDArray built from the tensor of type {@link DataType#DOUBLE}.
+ */
+ private static INDArray buildFromTensorDouble(Tensor<Double> tensor)
+ {
+ long[] tensorShape = tensor.shape();
+ int totalSize = 1;
+ for (long i : tensorShape) {totalSize *= i;}
+ double[] flatImageArray = new double[totalSize];
+ DoubleBuffer outBuff = DoubleBuffer.wrap(flatImageArray);
+ tensor.writeTo(outBuff);
+ outBuff = null;
+ return Nd4j.create(flatImageArray, tensorShape, DataType.DOUBLE);
+ }
+}
diff --git a/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/TensorBuilder.java b/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/TensorBuilder.java
index 3332be6..fb4977c 100644
--- a/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/TensorBuilder.java
+++ b/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/TensorBuilder.java
@@ -1,10 +1,11 @@
package org.bioimageanalysis.icy.tensorflow.v1.tensor;
-import org.nd4j.linalg.api.buffer.DataType;
-import org.nd4j.linalg.api.ndarray.INDArray;
import org.tensorflow.Tensor;
import org.tensorflow.types.UInt8;
+import net.imglib2.RandomAccessibleInterval;
+import net.imglib2.type.Type;
+
/**
* A TensorFlow {@link Tensor} builder for {@link INDArray} and {@link org.bioimageanalysis.icy.deeplearning.tensor.Tensor} objects.
*
@@ -35,7 +36,7 @@ public final class TensorBuilder
}
/**
- * Creates a {@link Tensor} based on the provided {@link INDArray} and the desired dimension order for the resulting tensor.
+ * Creates a {@link Tensor} based on the provided {@link RandomAccessibleInterval} and the desired dimension order for the resulting tensor.
*
* @param ndarray
* The NDArray to be converted.
@@ -43,7 +44,7 @@ public final class TensorBuilder
* @throws IllegalArgumentException
* If the ndarray type is not supported.
*/
- public static Tensor<?> build(INDArray ndarray)
+ public static <T extends Type<T>> Tensor<?> build(RandomAccessibleInterval<T> ndarray)
{
if (ndarray.dataType() == DataType.INT8 || ndarray.dataType() == DataType.UINT8) {
return buildByte(ndarray);
--
GitLab