Bumps TF version to 2.20

.github/workflows/build.yml

@@ -139,55 +139,9 @@ jobs:
       - name: Deploy native artifact
         if: env.DEPLOY_RELEASE == 'true' || env.DEPLOY_SNAPSHOT == 'true'
         run: mvn -f tensorflow-core/tensorflow-core-native/pom.xml deploy:deploy-file@native-only -B -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} -Durl=${{ needs.prepare.outputs.repositoryUrl }}
-  windows-x86_64:
-    runs-on: windows-2022
-    needs: prepare
-    strategy:
-       matrix:
-         ext: [""] #, -gpu]
-    steps:
-      - name: Install environment
-        shell: cmd
-        run: |
-          set "PATH=C:\msys64\usr\bin;%PATH%"
-          python -m pip install numpy six
-          set "EXT=${{ matrix.ext }}"
-          echo %JAVA_HOME%
-      - name: Configure Java
-        uses: actions/setup-java@v5
-        with:
-          distribution: 'adopt'
-          java-version: '11'
-      - name: Checkout repository
-        uses: actions/checkout@v6
-      - name: Build project
-        shell: cmd
-        run: |
-          call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" amd64
-          set "PATH=C:\msys64\usr\bin;%PATH%"
-          echo Shorten work paths to prevent Bazel from reaching MAX_PATH limit
-          mkdir C:\tmp
-          set "TEST_TMPDIR=C:\tmp"
-          set "TMPDIR=C:\tmp"
-          set "TEMP=C:\tmp"
-          set "TMP=C:\tmp"      
-          bash --version
-          git --version
-          cl
-          call mvn -version
-          echo ^<settings^>^<servers^>^<server^>^<id^>ossrh^</id^>^<username^>${{ secrets.CI_DEPLOY_USERNAME }}^</username^>^<password^>${{ secrets.CI_DEPLOY_PASSWORD }}^</password^>^</server^>^</servers^>^</settings^> > %USERPROFILE%\.m2\settings.xml
-          set "SKIP_EXPORT=true"
-          call mvn clean install -pl "!tensorflow-framework" -B -U -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }}
-          if ERRORLEVEL 1 exit /b
-      - name: Deploy native artifact
-        if: env.DEPLOY_RELEASE == 'true' || env.DEPLOY_SNAPSHOT == 'true'
-        shell: cmd
-        run: |
-          call mvn -f tensorflow-core/tensorflow-core-native/pom.xml deploy:deploy-file@native-only -B -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} -Durl=${{ needs.prepare.outputs.repositoryUrl }}
-          if ERRORLEVEL 1 exit /b
   deploy:
     if: ${{ github.event_name == 'push' && (github.ref == 'refs/heads/master' || github.ref == 'refs/heads/staging') }} # DEPLOY_SNAPSHOT (releases should be signed and deployed manually from local machine)
-    needs: [linux-x86_64, windows-x86_64, macosx-arm64, linux-arm64]
+    needs: [linux-x86_64, macosx-arm64, linux-arm64]
     runs-on: ubuntu-22.04
     steps:
       - name: Configure Java

README.md

@@ -60,7 +60,7 @@ only binaries for the following are being **supported and distributed** by this
 - `linux-x86_64-gpu`: Linux platforms on Intel/AMD chips with Cuda GPU support
 - `linux-arm64`: Linux platforms on Arm chips
 - `macosx-arm64`: MacOS X platforms on Apple Silicon chips
-- `windows-x86_64`: Windows platforms on Intel/AMD chips
+- `windows-x86_64`: Windows platforms on Intel/AMD chips (v1.1.0 and earlier)
 
 Binaries for `macosx-x86_64` are available for TF-Java 1.0 series releases and earlier, they were dropped from
 TF-Java 1.1 and newer as they are no longer supported or released by Google.
@@ -215,7 +215,7 @@ This table shows the mapping between TensorFlow, TensorFlow Java and minimum sup
 | 1.0.0-rc.2              | 2.16.2             | 11                   |
 | 1.0.0                   | 2.16.2             | 11                   |
 | 1.1.0                   | 2.18.0             | 11                   |
-| 1.2.0-SNAPSHOT          | 2.18.0             | 11                   |
+| 1.2.0-SNAPSHOT          | 2.20.0             | 11                   |
 
 ## How to Contribute?
 

tensorflow-core/pom.xml

@@ -42,7 +42,7 @@
     https://github.com/tensorflow/tensorflow/blob/master/tensorflow/workspace2.bzl
     (but for the currently used release, not master)
     -->
-    <protobuf.version>3.21.9</protobuf.version>
+    <protobuf.version>4.28.3</protobuf.version>
 
     <native.classifier>${javacpp.platform}${javacpp.platform.extension}</native.classifier>
     <javacpp.platform.extension></javacpp.platform.extension>

tensorflow-core/tensorflow-core-api/scripts/test_download.sh

@@ -5,13 +5,13 @@ DOWNLOAD_FOLDER="$1"
 
 case ${PLATFORM:-} in
   'linux-x86_64')
-    TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/f3/73/3a906feb0d71d9353c6fb2363d4052856cc6eff5a78a097b1a6002d4e908/tensorflow_text-2.18.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl'
+    TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/c3/e6/cfd784298ffb759a4235721cac2ac20f7ff758bf687069cfbaebb06c5804/tensorflow_text-2.20.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl'
     ;;
   'linux-arm64')
-    TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/8a/9a/ebba9f6274f8b51e5fe1ac2411b8b6bf680a32d10bd6e9c54be1faeec062/tensorflow_text-2.18.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl'
+    TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/f5/ca/796cfd97ae6693d3c84c37575a6d481be5f1ef36c920d1a73c884f31797b/tensorflow_text-2.20.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl'
     ;;
   'macosx-arm64')
-    TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/18/b6/8ad233edb0732847db1da538cea941dcccc42f59304ff6fb449676e6dd5a/tensorflow_text-2.18.1-cp311-cp311-macosx_11_0_arm64.whl'
+    TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/98/e4/e3c72d0a73caeba90cf5b31e69d44e9a08d614e0e829484d813f3b63e037/tensorflow_text-2.20.0-cp312-cp312-macosx_11_0_arm64.whl'
     ;;
   *)
     echo "TensorFlow Text distribution for ${PLATFORM} is not supported for download"

tensorflow-core/tensorflow-core-api/src/api/api_def_DecodeWebP.pbtxt

@@ -0,0 +1,6 @@
+op {
+  graph_op_name: "DecodeWebP"
+  endpoint {
+    name: "image.DecodeWebP"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_TPUDummyInput.pbtxt

@@ -0,0 +1,7 @@
+op {
+  graph_op_name: "TPUDummyInput"
+  visibility: HIDDEN
+  endpoint {
+    name: "tpu.TPUDummyInput"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_XlaSparseActivationsUnstack.pbtxt

@@ -0,0 +1,7 @@
+op {
+  graph_op_name: "XlaSparseActivationsUnstack"
+  visibility: VISIBLE
+  endpoint {
+    name: "xla.XlaSparseActivationsUnstack"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput.pbtxt

@@ -0,0 +1,7 @@
+op {
+  graph_op_name: "XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput"
+  visibility: VISIBLE
+  endpoint {
+    name: "xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradAndCsrInput"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput.pbtxt

@@ -0,0 +1,7 @@
+op {
+  graph_op_name: "XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput"
+  visibility: VISIBLE
+  endpoint {
+    name: "xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdagradMomentumAndCsrInput"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput.pbtxt

@@ -0,0 +1,7 @@
+op {
+  graph_op_name: "XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput"
+  visibility: VISIBLE
+  endpoint {
+    name: "xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithAdamAndCsrInput"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_XlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput.pbtxt

@@ -0,0 +1,7 @@
+op {
+  graph_op_name: "XlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput"
+  visibility: VISIBLE
+  endpoint {
+    name: "xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithCsrInput"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_XlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput.pbtxt

@@ -0,0 +1,7 @@
+op {
+  graph_op_name: "XlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput"
+  visibility: VISIBLE
+  endpoint {
+    name: "xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithFtrlAndCsrInput"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_XlaSparseDenseMatmulCustomCombinerOnTcGradWithSgdAndCsrInput.pbtxt

@@ -0,0 +1,6 @@
+op {
+  graph_op_name: "XlaSparseDenseMatmulCustomCombinerOnTcGradWithSgdAndCsrInput"
+  endpoint {
+    name: "xla.XlaSparseDenseMatmulCustomCombinerOnTcGradWithSgdAndCsrInput"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_XlaSparseDenseMatmulCustomCombinerOnTcWithCsrInput.pbtxt

@@ -0,0 +1,6 @@
+op {
+  graph_op_name: "XlaSparseDenseMatmulCustomCombinerOnTcWithCsrInput"
+  endpoint {
+    name: "xla.XlaSparseDenseMatmulCustomCombinerOnTcWithCsrInput"
+  }
+}

tensorflow-core/tensorflow-core-api/src/api/api_def_XlaSparseGradientsStack.pbtxt

@@ -0,0 +1,6 @@
+op {
+  graph_op_name: "XlaSparseGradientsStack"
+  endpoint {
+    name: "xla.XlaSparseGradientsStack"
+  }
+}

tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java

@@ -44,7 +44,7 @@ public final class DtypesOps {
    * Converts each entry in the given tensor to strings.
    *  Supports many numeric types and boolean.
    *  <p>For Unicode, see the
-   *  [https://www.tensorflow.org/tutorials/representation/unicode](Working with Unicode text)
+   *  [https://www.tensorflow.org/text/guide/unicode](Working with Unicode text)
    *  tutorial.
    *  <p>Examples:
    *  <blockquote>

tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java

@@ -32,6 +32,7 @@
 import org.tensorflow.op.image.DecodeImage;
 import org.tensorflow.op.image.DecodeJpeg;
 import org.tensorflow.op.image.DecodePng;
+import org.tensorflow.op.image.DecodeWebP;
 import org.tensorflow.op.image.DrawBoundingBoxes;
 import org.tensorflow.op.image.EncodeJpeg;
 import org.tensorflow.op.image.EncodeJpegVariableQuality;
@@ -336,17 +337,18 @@ public DecodeGif decodeGif(Operand<TString> contents) {
   }
 
   /**
-   * Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
-   *  Detects whether an image is a BMP, GIF, JPEG, or PNG, and performs the
+   * Function for decode_bmp, decode_gif, decode_jpeg, decode_webp, and decode_png.
+   *  Detects whether an image is a BMP, GIF, JPEG, WebP, or PNG, and performs the
    *  appropriate operation to convert the input bytes string into a Tensor of type
    *  dtype.
-   *  <p><em>NOTE</em>: decode_gif returns a 4-D array [num_frames, height, width, 3], as
-   *  opposed to decode_bmp, decode_jpeg and decode_png, which return 3-D arrays
-   *  [height, width, num_channels]. Make sure to take this into account when
-   *  constructing your graph if you are intermixing GIF files with BMP, JPEG, and/or
-   *  PNG files. Alternately, set the expand_animations argument of this function to
-   *  False, in which case the op will return 3-dimensional tensors and will truncate
-   *  animated GIF files to the first frame.
+   *  <p><em>NOTE</em>: decode_gif and decode_webp return a 4-D
+   *  array [num_frames, height, width, 3], as opposed to decode_bmp,
+   *  decode_jpeg, and decode_png, which always return 3-D arrays [height,
+   *  width, num_channels]. Make sure to take this into account when
+   *  constructing your graph if you are intermixing animated files with
+   *  BMP, JPEG, and/or PNG files. Alternately, set the expand_animations
+   *  argument of this function to False, in which case the op will return
+   *  3-dimensional tensors and will truncate animations to the first frame.
    *  <p><em>NOTE</em>: If the first frame of an animated GIF does not occupy the entire
    *  canvas (maximum frame width x maximum frame height), then it fills the
    *  unoccupied areas (in the first frame) with zeros (black). For frames after the
@@ -357,22 +359,24 @@ public DecodeGif decodeGif(Operand<TString> contents) {
    * @param options carries optional attribute values
    * @return a new instance of DecodeImage, with default output types
    */
-  public DecodeImage<TUint8> decodeImage(Operand<TString> contents, DecodeImage.Options[] options) {
+  public DecodeImage<TUint8> decodeImage(Operand<TString> contents,
+      DecodeImage.Options... options) {
     return DecodeImage.create(scope, contents, options);
   }
 
   /**
-   * Function for decode_bmp, decode_gif, decode_jpeg, and decode_png.
-   *  Detects whether an image is a BMP, GIF, JPEG, or PNG, and performs the
+   * Function for decode_bmp, decode_gif, decode_jpeg, decode_webp, and decode_png.
+   *  Detects whether an image is a BMP, GIF, JPEG, WebP, or PNG, and performs the
    *  appropriate operation to convert the input bytes string into a Tensor of type
    *  dtype.
-   *  <p><em>NOTE</em>: decode_gif returns a 4-D array [num_frames, height, width, 3], as
-   *  opposed to decode_bmp, decode_jpeg and decode_png, which return 3-D arrays
-   *  [height, width, num_channels]. Make sure to take this into account when
-   *  constructing your graph if you are intermixing GIF files with BMP, JPEG, and/or
-   *  PNG files. Alternately, set the expand_animations argument of this function to
-   *  False, in which case the op will return 3-dimensional tensors and will truncate
-   *  animated GIF files to the first frame.
+   *  <p><em>NOTE</em>: decode_gif and decode_webp return a 4-D
+   *  array [num_frames, height, width, 3], as opposed to decode_bmp,
+   *  decode_jpeg, and decode_png, which always return 3-D arrays [height,
+   *  width, num_channels]. Make sure to take this into account when
+   *  constructing your graph if you are intermixing animated files with
+   *  BMP, JPEG, and/or PNG files. Alternately, set the expand_animations
+   *  argument of this function to False, in which case the op will return
+   *  3-dimensional tensors and will truncate animations to the first frame.
    *  <p><em>NOTE</em>: If the first frame of an animated GIF does not occupy the entire
    *  canvas (maximum frame width x maximum frame height), then it fills the
    *  unoccupied areas (in the first frame) with zeros (black). For frames after the
@@ -436,7 +440,7 @@ public DecodeJpeg decodeJpeg(Operand<TString> contents, DecodeJpeg.Options... op
    * @param options carries optional attribute values
    * @return a new instance of DecodePng, with default output types
    */
-  public DecodePng<TUint8> decodePng(Operand<TString> contents, DecodePng.Options[] options) {
+  public DecodePng<TUint8> decodePng(Operand<TString> contents, DecodePng.Options... options) {
     return DecodePng.create(scope, contents, options);
   }
 
@@ -467,6 +471,51 @@ public <T extends TNumber> DecodePng<T> decodePng(Operand<TString> contents, Cla
     return DecodePng.create(scope, contents, dtype, options);
   }
 
+  /**
+   * Decode a WebP-encoded image to a uint8 tensor.
+   *  The attr {@code channels} indicates the desired number of color channels for the
+   *  decoded image.
+   *  <p>Accepted values are:
+   *  <ul>
+   *  <li>0: Use the number of channels in the WebP-encoded image.</li>
+   *  <li>3: output an RGB image.</li>
+   *  <li>4: output an RGBA image.</li>
+   *  </ul>
+   *  <p>The number of channels must currently match that of the underlying file.
+   *  For WebP animations, only 4-channel RGBA is supported.
+   *
+   * @param contents 0-D.  The WebP-encoded image.
+   * @param options carries optional attribute values
+   * @return a new instance of DecodeWebP, with default output types
+   */
+  public DecodeWebP<TUint8> decodeWebP(Operand<TString> contents, DecodeWebP.Options... options) {
+    return DecodeWebP.create(scope, contents, options);
+  }
+
+  /**
+   * Decode a WebP-encoded image to a uint8 tensor.
+   *  The attr {@code channels} indicates the desired number of color channels for the
+   *  decoded image.
+   *  <p>Accepted values are:
+   *  <ul>
+   *  <li>0: Use the number of channels in the WebP-encoded image.</li>
+   *  <li>3: output an RGB image.</li>
+   *  <li>4: output an RGBA image.</li>
+   *  </ul>
+   *  <p>The number of channels must currently match that of the underlying file.
+   *  For WebP animations, only 4-channel RGBA is supported.
+   *
+   * @param contents 0-D.  The WebP-encoded image.
+   * @param dtype The value of the dtype attribute
+   * @param options carries optional attribute values
+   * @param <T> data type for {@code DecodeWebP} output and operands
+   * @return a new instance of DecodeWebP
+   */
+  public <T extends TNumber> DecodeWebP<T> decodeWebP(Operand<TString> contents, Class<T> dtype,
+      DecodeWebP.Options... options) {
+    return DecodeWebP.create(scope, contents, dtype, options);
+  }
+
   /**
    * Draw bounding boxes on a batch of images.
    *  Outputs a copy of {@code images} but draws on top of the pixels zero or more bounding

tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java

@@ -2127,7 +2127,7 @@ public <T extends TNumber> MaxPoolGradWithArgmax<T> maxPoolGradWithArgmax(Operan
    * @return a new instance of MaxPoolWithArgmax, with default output types
    */
   public <T extends TNumber> MaxPoolWithArgmax<T, TInt64> maxPoolWithArgmax(Operand<T> input,
-      List<Long> ksize, List<Long> strides, String padding, MaxPoolWithArgmax.Options[] options) {
+      List<Long> ksize, List<Long> strides, String padding, MaxPoolWithArgmax.Options... options) {
     return MaxPoolWithArgmax.create(scope, input, ksize, strides, padding, options);
   }
 

tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java

@@ -420,10 +420,10 @@ public final class Ops {
 
   public final SummaryOps summary;
 
-  public final ImageOps image;
-
   public final RaggedOps ragged;
 
+  public final ImageOps image;
+
   public final ShapeOps shape;
 
   public final IoOps io;
@@ -457,8 +457,8 @@ public final class Ops {
     train = new TrainOps(this);
     quantization = new QuantizationOps(this);
     summary = new SummaryOps(this);
-    image = new ImageOps(this);
     ragged = new RaggedOps(this);
+    image = new ImageOps(this);
     shape = new ShapeOps(this);
     io = new IoOps(this);
     dtypes = new DtypesOps(this);

tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java

@@ -114,7 +114,7 @@ public final class QuantizationOps {
    * @return a new instance of Dequantize, with default output types
    */
   public Dequantize<TFloat32> dequantize(Operand<? extends TNumber> input,
-      Operand<TFloat32> minRange, Operand<TFloat32> maxRange, Dequantize.Options[] options) {
+      Operand<TFloat32> minRange, Operand<TFloat32> maxRange, Dequantize.Options... options) {
     return Dequantize.create(scope, input, minRange, maxRange, options);
   }
 

tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java

@@ -210,7 +210,7 @@ public LogUniformCandidateSampler logUniformCandidateSampler(Operand<TInt64> tru
    * @return a new instance of Multinomial, with default output types
    */
   public Multinomial<TInt64> multinomial(Operand<? extends TNumber> logits,
-      Operand<TInt32> numSamples, Multinomial.Options[] options) {
+      Operand<TInt32> numSamples, Multinomial.Options... options) {
     return Multinomial.create(scope, logits, numSamples, options);
   }
 
@@ -327,7 +327,7 @@ public <T extends TNumber> RandomGammaGrad<T> randomGammaGrad(Operand<T> alpha,
    * @return a new instance of RandomPoisson, with default output types
    */
   public RandomPoisson<TInt64> randomPoisson(Operand<? extends TNumber> shape,
-      Operand<? extends TNumber> rate, RandomPoisson.Options[] options) {
+      Operand<? extends TNumber> rate, RandomPoisson.Options... options) {
     return RandomPoisson.create(scope, shape, rate, options);
   }