final int exitValue = currentProcess.exitValue();

            if (logger.isInfoEnabled()) {
                logger.info("Python: Exit Code={} - Process Output:\n{}", exitValue, it.getOutput());
            }
            if (exitValue != 0) {
                final StringBuilder out = new StringBuilder();
                if (processTimeout) {

        }

        @Override
        public ExecutionOutcome getOutcome() {
            return mode;
        }

        @Override
        public Object getOutput(File workspace) {
            return workOutput.getOutput(workspace);
        }

        @Override
        public boolean canStoreOutputsInCache() {
            return workOutput.canStoreInCache();
        }
    }

      return failure();
    }
    // Only push down the dequantize op when the output is smaller, so that it
    // can have smaller memory usage.
    auto input_type =
        mlir::dyn_cast<RankedTensorType>(dequantize_op.getOutput().getType());
    auto output_type = mlir::dyn_cast<RankedTensorType>(
        passthrough_op->getResult(0).getType());
    if (!input_type || !output_type ||

    FloatAttr max = mlir::dyn_cast_or_null<FloatAttr>(op->getAttr("max"));

    // When there are no min and max attributes, remove op.
    if (min == nullptr || max == nullptr) {
      op.getOutput().replaceAllUsesWith(op.getInput());
      rewriter.eraseOp(op);
      return success();
    }

    // The layer stats contain only the first min/max pairs.
    ElementsAttr layer_stats = DenseFPElementsAttr::get(

        pluginSourceSet.getJava().srcDir(generatePluginAdapters.flatMap(GeneratePluginAdaptersTask::getPluginAdapterSourcesOutputDirectory));
        pluginSourceSet.getOutput().dir(precompilePlugins.flatMap(CompileGroovyScriptPluginsTask::getPrecompiledGroovyScriptsOutputDirectory));
        pluginSourceSet.getOutput().dir(extractPluginRequests.flatMap(ExtractPluginRequestsTask::getExtractedPluginRequestsClassesStagingDirectory));
    }

            .withPluginClasspath()
            .withArguments("greet")
            .withProjectDir(projectDir)
            .build();

        // Verify the result
        assertTrue(result.getOutput().contains("Hello from plugin 'com.example.plugin.greeting'"));
    }

    private void writeString(File file, String string) throws IOException {
        try (Writer writer = new FileWriter(file)) {

class MyTask extends DefaultTask {
    @Nested
    TextResource config

    @OutputFile
    File output

    @TaskAction
    void generate() {
        getOutput().text = getConfig().asString()
    }
}

def generateConfigFile = tasks.register("generateConfigFile") {
    outputs.file "config.txt"
    doLast {
        file("config.txt").text = "my config"
    }
}

task generateConfigZip(type: Zip) {

        tensor_proto_attr.getValue(),
        mlir::dyn_cast<TensorType>(ToLegalType(op.getOutput().getType())));
    if (failed(dense_attr_or)) {
      op->emitError("failed to get DenseElementAttr.");
      return failure();
    }

    rewriter.replaceOpWithNewOp<TF::ConstOp>(
        op, ToLegalType(op.getOutput().getType()), *dense_attr_or);
    return success();
  }
};

struct ConvertTFQuantTypes

        runner.withArguments("greeting");
        runner.withProjectDir(projectDir);
        BuildResult result = runner.build();

        // Verify the result
        assertTrue(result.getOutput().contains("Hello from plugin '${pluginId.value}'"));
    }

    private void writeString(File file, String string) throws IOException {
        try (Writer writer = new FileWriter(file)) {
            writer.write(string);

        variant.getAttributes().attribute(LibraryElements.LIBRARY_ELEMENTS_ATTRIBUTE, objectFactory.named(LibraryElements.class, LibraryElements.RESOURCES));
        DefaultSourceSetOutput output = Cast.uncheckedCast(sourceSet.getOutput());
        DefaultSourceSetOutput.DirectoryContribution resourcesContribution = output.getResourcesContribution();
        if (resourcesContribution != null) {