Precompiled and packaged tensorflow for java.
The jar tensorflow-core-platform-0.4.0-SNAPSHOT.jar was shaded, so they include the other dependencies for tensorflow-java.
To download the jars, head to the releases.
Based on this branch: https://github.com/Craigacp/tensorflow-java/tree/apple-silicon
Built on Macbook Air M1 (2020) on macOS Monterey.
@DevinTDHa , I tried your jars and am having issues. First I tried including them as a Gradle dependency, and they didn't work. I got Unresolved reference: tensorflow. Next I tried checking my Gradle --debug info, and confirmed that each of your jars are in fact in my compile class path. Finally I decided to look inside the jars to, but could not do so. Running jar -tf on any of your jars gives me
java.util.zip.ZipException: zip END header not found
at java.base/java.util.zip.ZipFile$Source.findEND(ZipFile.java:1469)
at java.base/java.util.zip.ZipFile$Source.initCEN(ZipFile.java:1477)
at java.base/java.util.zip.ZipFile$Source.<init>(ZipFile.java:1315)
at java.base/java.util.zip.ZipFile$Source.get(ZipFile.java:1277)
at java.base/java.util.zip.ZipFile$CleanableResource.<init>(ZipFile.java:709)
at java.base/java.util.zip.ZipFile.<init>(ZipFile.java:243)
at java.base/java.util.zip.ZipFile.<init>(ZipFile.java:172)
at java.base/java.util.zip.ZipFile.<init>(ZipFile.java:143)
at jdk.jartool/sun.tools.jar.Main.list(Main.java:1484)
at jdk.jartool/sun.tools.jar.Main.run(Main.java:352)
at jdk.jartool/sun.tools.jar.Main.main(Main.java:1665)
Thanks for doing this work. Unfortunately I cannot access the jars from git lfs - I get the following error:
% git lfs pull
batch response: This repository is over its data quota. Account responsible for LFS bandwidth should purchase more data packs to restore access.
Failed to fetch some objects from 'https://github.com/DevinTDHa/precompiled-tf-jni-m1.git/info/lfs'
Depending on the cost I may be able to contribute something.
Hi @DevinTDHa
I'm trying to run the introductory Tensorflow example from https://www.tensorflow.org/jvm/install#example_program and use the precompiled binaries from the release 0.4.0-SNAPSHOT. When I run the command mvn compile exec:java, the JRE crashes with SIGILL error (Full log below). I'm running this example on a 2023 Apple M2 Pro with macOS Ventura 13.5.
I wanted to find out if these precompiled M1 binaries work for M2 processors? Or do we need to recompile them on M2 hardware separately?
Thanks!
---- Detailed log ----
[INFO] Compiling 1 source file to tensorflow-test/target/classes
[INFO]
[INFO] --- exec:3.1.0:java (default-cli) @ hellotensorflow ---
#
# A fatal error has been detected by the Java Runtime Environment:
#
# SIGILL (0x4) at pc=0x000000012bc419f5, pid=14525, tid=0x000000000000a11b
#
# JRE version: Java(TM) SE Runtime Environment (8.0_311-b11) (build 1.8.0_311-b11)
# Java VM: Java HotSpot(TM) 64-Bit Server VM (25.311-b11 mixed mode bsd-amd64 compressed oops)
# Problematic frame:
# C [libtensorflow_framework.2.dylib+0x1f9f5] tensorflow::monitoring::MetricDef<(tensorflow::monitoring::MetricKind)1, long long, 2>::MetricDef<char [11], char [7]>(absl::lts_20210324::string_view, absl::lts_20210324::string_view, char const (&) [11], char const (&) [7])+0x125
#
# Failed to write core dump. Core dumps have been disabled. To enable core dumping, try "ulimit -c unlimited" before starting Java again
#
# An error report file with more information is saved as:
# tensorflow-test/hs_err_pid14525.log
#
# If you would like to submit a bug report, please visit:
# http://bugreport.java.com/bugreport/crash.jsp
# The crash happened outside the Java Virtual Machine in native code.
# See problematic frame for where to report the bug.
#
[1] 14525 abort mvn compile exec:java
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