A. Unique TensorFlower <******@****.***> 1711560469 +0000

Doyeon Kim <******@****.***> 1708661614 -0800

        ),
    ],
    tblgen = "@llvm-project//mlir:mlir-tblgen",
    td_file = "ir/tf_ops.td",
    deps = [
        ":tensorflow_ops_td_files",
    ],
)

# We only shard tf_op on name for build performance reasons.
tf_ops_category_list = [
    {
        "name": "ops_a_m",
        "include": "tf.[A-M].*$",
    },
    {
        "name": "ops_n_z",
        "include": "tf.[N-Z].*$",
    },
]

A. Unique TensorFlower <******@****.***> 1711560469 +0000

Arturo Schmidt <******@****.***> 1718227424 -0700

Arturo Schmidt <******@****.***> 1717710156 -0700

Matthias Kramm <******@****.***> 1711664526 -0700

A. Unique TensorFlower <******@****.***> 1711560469 +0000

A. Unique TensorFlower <******@****.***> 1711560469 +0000

        }
        singleProjectBuildInSubfolder("includedBuild")

        when:
        def builds = withConnection {
            action(new FetchBuilds()).run()
        }

        then:
        builds.rootProject.name == ["root", "includedBuild"]
    }

    def "Can fetch project scoped models from included builds"() {
        given:
        multiProjectBuildInRootFolder("root", ["a", "b"]) {