* {@code :artifactId} if there is no conflict.
     * This method is made package-private for testing purposes.
     *
     * @param mavenProjects Maven projects which are part of build execution.
     * @param firstFailedProject The first project which has failed.
     * @return Value for -rf flag to resume build exactly from place where it failed ({@code :artifactId} in general

            if (logger.isDebugEnabled()) {
                logger.debug("Failed to process a scroll request.", e);
            }
            writeJsonResponse(HttpServletResponse.SC_BAD_REQUEST, e);
        } catch (final Exception e) {
            if (logger.isDebugEnabled()) {
                logger.debug("Failed to process a scroll request.", e);
            }

#     release_cpu_windows:             Toolchain and CUDA options for Windows CPU builds.

# Default build options. These are applied first and unconditionally.

# For projects which use TensorFlow as part of a Bazel build process, putting
# nothing in a bazelrc will default to a monolithic build. The following line
# opts in to modular op registration support by default.
build --define framework_shared_object=true

                // only allow ${basedir}, ${project.basedir} or ${project.baseUri}
                Matcher m = EXPRESSION_NAME_PATTERN.matcher(repository.getUrl());
                while (m.find()) {
                    if (!("basedir".equals(m.group(1))
                            || "project.basedir".equals(m.group(1))
                            || "project.baseUri".equals(m.group(1)))) {

								<path>${project.build.directory}/fess/WEB-INF/classes/fess_config.properties</path>
								<path>${project.build.directory}/fess/WEB-INF/classes/fess_env_crawler.properties</path>
								<path>${project.build.directory}/fess/WEB-INF/classes/fess_env_suggest.properties</path>
								<path>${project.build.directory}/fess/WEB-INF/classes/fess_env_thumbnail.properties</path>

				"subprojects":[
					"launcher",
					"build-state",
					"time",
					"logging-api",
					"public-api-tests",
					"kotlin-dsl-plugins",
					"serialization",
					"toolchains-jvm-shared",
					"build-process-services",
					"docs-asciidoctor-extensions-base",
					"internal-instrumentation-processor"
				]
			},
			{
				"parallelizationMethod":{
					"name":"TestDistribution"
				},
				"subprojects":[

				"application/vnd.ms-powerpoint.slide.macroenabled.12",
				"application/vnd.ms-powerpoint.slideshow.macroenabled.12",
				"application/vnd.ms-powerpoint.template.macroenabled.12",
				"application/vnd.ms-project",
				"application/x-project",
				"application/vnd.ms-tnef",
				"application/vnd.ms-wmdrm.lic-chlg-req",
				"application/vnd.ms-wmdrm.lic-resp",
				"application/vnd.ms-wmdrm.meter-chlg-req",

// named job. The server can communicate with any other server in the same
// cluster.

// In-process TensorFlow server.
typedef struct TF_Server TF_Server;

// Creates a new in-process TensorFlow server configured using a serialized
// ServerDef protocol buffer provided via `proto` and `proto_len`.
//

/*
 * Copyright 2012-2024 CodeLibs Project and the Others.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

# build is static and TensorFlow symbols (in Python only) are loaded into the
# global symbol table in order to support op registration. This means that
# projects building with Bazel and importing TensorFlow as a dependency will not
# depend on libtensorflow_framework.so unless they opt in.
tf_cc_shared_library(
    name = "tensorflow_framework",
    additional_linker_inputs = [