diff --git a/pom.xml b/pom.xml
index 102d51e0149..66687aade72 100644
--- a/pom.xml
+++ b/pom.xml
@@ -46,7 +46,7 @@
true
true
true
- 2.11.1
+ 2.20.2
@@ -371,7 +371,9 @@
-
+
+ 1.14.0
+
diff --git a/tensorflow-core/pom.xml b/tensorflow-core/pom.xml
index 54b8ab8372f..7d3dd3ca324 100644
--- a/tensorflow-core/pom.xml
+++ b/tensorflow-core/pom.xml
@@ -43,7 +43,7 @@
Bumped to newer version to patch a CVE only present in protobuf-java
-->
- 3.19.2
+ 3.19.4
${javacpp.platform}${javacpp.platform.extension}
false
diff --git a/tensorflow-framework/pom.xml b/tensorflow-framework/pom.xml
index 026bf227afe..b0d4900fb1d 100644
--- a/tensorflow-framework/pom.xml
+++ b/tensorflow-framework/pom.xml
@@ -93,7 +93,7 @@
1
false
- -Xmx2G -XX:MaxPermSize=256m
+ -Xmx2G
**/*Test.java
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/PrecisionAtRecallTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/PrecisionAtRecallTest.java
index 8132b74d7cd..756a7651363 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/PrecisionAtRecallTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/PrecisionAtRecallTest.java
@@ -24,7 +24,6 @@
import org.tensorflow.ndarray.Shape;
import org.tensorflow.op.Op;
import org.tensorflow.op.Ops;
-import org.tensorflow.op.random.RandomUniform;
import org.tensorflow.types.TFloat32;
import org.tensorflow.types.TInt64;
@@ -39,11 +38,11 @@ public void testValueIsIdempotent() {
PrecisionAtRecall instance = new PrecisionAtRecall<>(0.7f, 1001L, TFloat32.class);
Operand predictions =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
Operand labels =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
Op update = instance.updateState(tf, labels, predictions, null);
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/PrecisionTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/PrecisionTest.java
index b195432115e..673a563f894 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/PrecisionTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/PrecisionTest.java
@@ -22,7 +22,6 @@
import org.tensorflow.ndarray.Shape;
import org.tensorflow.op.Op;
import org.tensorflow.op.Ops;
-import org.tensorflow.op.random.RandomUniform;
import org.tensorflow.types.TFloat32;
import org.tensorflow.types.TFloat64;
import org.tensorflow.types.TInt32;
@@ -39,11 +38,11 @@ public void testValueIsIdempotent() {
Precision instance =
new Precision<>(new float[] {0.3f, 0.72f}, 1001L, TFloat64.class);
Operand predictions =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1001L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1001L, 0L}), TFloat32.class);
Operand labels =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1001L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1001L, 0L}), TFloat32.class);
Op update = instance.updateState(tf, labels, predictions, null);
@@ -81,7 +80,11 @@ public void testUnweightedAllIncorrect() {
Precision instance = new Precision<>(0.5f, 1001L, TFloat32.class);
Operand predictions =
- tf.random.randomUniformInt(tf.constant(Shape.of(100, 1)), tf.constant(0), tf.constant(2));
+ tf.random.statelessMultinomial(
+ tf.constant(new float[][] {{0.5f, 0.5f}}),
+ tf.constant(100),
+ tf.constant(new long[] {1001L, 0L}),
+ TInt32.class);
Operand labels = tf.math.sub(tf.constant(1), predictions);
Op update = instance.updateState(tf, labels, predictions, null);
session.run(update);
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/RecallAtPrecisionTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/RecallAtPrecisionTest.java
index 36dba3180b7..184c42b7326 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/RecallAtPrecisionTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/RecallAtPrecisionTest.java
@@ -24,7 +24,6 @@
import org.tensorflow.ndarray.Shape;
import org.tensorflow.op.Op;
import org.tensorflow.op.Ops;
-import org.tensorflow.op.random.RandomUniform;
import org.tensorflow.types.TFloat32;
import org.tensorflow.types.TInt64;
@@ -39,11 +38,11 @@ public void testValueIsIdempotent() {
RecallAtPrecision instance = new RecallAtPrecision<>(0.7f, 1001L, TFloat32.class);
Operand predictions =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
Operand labels =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
labels = tf.math.mul(labels, tf.constant(2.0f));
Op update = instance.updateState(tf, labels, predictions);
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/RecallTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/RecallTest.java
index e820cbe0d74..e862ffe280e 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/RecallTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/RecallTest.java
@@ -36,9 +36,11 @@ public void testValueIsIdempotent() {
Recall instance = new Recall<>(new float[] {0.3f, 0.72f}, 1001L, TFloat32.class);
Operand predictions =
- tf.random.randomUniform(tf.constant(Shape.of(10, 3)), TFloat32.class);
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
Operand labels =
- tf.random.randomUniform(tf.constant(Shape.of(10, 3)), TFloat32.class);
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
Op update = instance.updateState(tf, labels, predictions, null);
for (int i = 0; i < 10; i++) session.run(update);
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/SensitivityAtSpecificityTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/SensitivityAtSpecificityTest.java
index d18ca9813fe..179dbf2b9fc 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/SensitivityAtSpecificityTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/SensitivityAtSpecificityTest.java
@@ -24,7 +24,6 @@
import org.tensorflow.ndarray.Shape;
import org.tensorflow.op.Op;
import org.tensorflow.op.Ops;
-import org.tensorflow.op.random.RandomUniform;
import org.tensorflow.types.TFloat32;
import org.tensorflow.types.TFloat64;
import org.tensorflow.types.TInt64;
@@ -40,11 +39,11 @@ public void testValueIsIdempotent() {
SensitivityAtSpecificity instance =
new SensitivityAtSpecificity<>(0.7f, 1001L, TFloat32.class);
Operand predictions =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
Operand labels =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
labels = tf.math.mul(labels, tf.constant(2.0f));
// instance.setDebug(session.getGraphSession());
diff --git a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/SpecificityAtSensitivityTest.java b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/SpecificityAtSensitivityTest.java
index 676b443cd1c..6507345bbb4 100644
--- a/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/SpecificityAtSensitivityTest.java
+++ b/tensorflow-framework/src/test/java/org/tensorflow/framework/metrics/SpecificityAtSensitivityTest.java
@@ -24,7 +24,6 @@
import org.tensorflow.ndarray.Shape;
import org.tensorflow.op.Op;
import org.tensorflow.op.Ops;
-import org.tensorflow.op.random.RandomUniform;
import org.tensorflow.types.TFloat32;
import org.tensorflow.types.TFloat64;
import org.tensorflow.types.TInt32;
@@ -42,11 +41,11 @@ public void testValueIsIdempotent() {
new SpecificityAtSensitivity<>(0.7f, 1001L, TFloat32.class);
Operand predictions =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
Operand labels =
- tf.random.randomUniform(
- tf.constant(Shape.of(10, 3)), TFloat32.class, RandomUniform.seed(1L));
+ tf.random.statelessRandomUniform(
+ tf.constant(Shape.of(10, 3)), tf.constant(new long[] {1L, 0L}), TFloat32.class);
// instance.setDebug(session.getGraphSession());
Op update = instance.updateState(tf, labels, predictions, null);