Just to help out some other people, here is the gist of it. The solution does prerequires having setup for bazel the (1) python headers and (2) pip requirements and (3) cuda.
Create a .bzl file containing something like
load("@local_config_cuda//cuda:build_defs.bzl", "if_cuda")
load("@local_config_cuda//cuda:build_defs.bzl", "cuda_default_copts")

load("@pip_deps//:requirements.bzl", "requirement")

def pytorch_cpp_extension(name, srcs=[], gpu_srcs=[], deps=[], copts=[], defines=[],  
                          binary=True, linkopts=[]):
    """Create a pytorch cpp extension as a cpp and importable python library.
    
    All options defined below should stay close to the official torch cpp extension options as
    defined in https://github.com/pytorch/pytorch/blob/master/torch/utils/cpp_extension.py.
    """
    name_so = name + ".so"
    torch_deps = [
        requirement("torch", target = "cpp"),
    ]

    cuda_deps = [
        "@local_config_cuda//cuda:cudart_static",
        "@local_config_cuda//cuda:cuda_headers",
    ]

    copts = copts +[
        "-fPIC",
        "-D_GLIBCXX_USE_CXX11_ABI=0",
        "-DTORCH_API_INCLUDE_EXTENSION_H",
        "-fno-strict-aliasing",
        "-fopenmp",
        "-fstack-protector-strong",
        "-fwrapv",
        "-O2",
        "-std=c++14",
        "-DTORCH_EXTENSION_NAME=" + name
    ]

    if gpu_srcs:
        native.cc_library(
            name = name_so + "_gpu",
            srcs = gpu_srcs,
            deps = deps + torch_deps + if_cuda(cuda_deps),
            copts = copts + cuda_default_copts(),
            defines = defines,
            linkopts = linkopts,
        )
        cuda_deps.extend([":" + name_so + "_gpu"])

    if binary:
        native.cc_binary(
            name = name_so,
            srcs = srcs,
            deps = deps + torch_deps + if_cuda(cuda_deps),
            linkshared = 1,
            copts = copts,
            defines = defines,
            linkopts = linkopts,
        )
    else:
        native.cc_library(
            name = name_so,
            srcs = srcs,
            deps = deps + torch_deps + if_cuda(cuda_deps),
            copts = copts,
            defines = defines,
            linkopts = linkopts,
        )

    native.py_library(
        name = name,
        data = [":" + name_so],
    )

And be sure you can actually require torch as a cpp target library like like so;
genrule_directory(
    name = "include",
    srcs = [":extracted"],
    cmd = "mkdir -p $@ && cp -a $</torch/lib/include/. $@",
)

# NOTE: Make sure this yields the same includes as `include_paths()`:
# See https://github.com/pytorch/pytorch/blob/master/torch/utils/cpp_extension.py#L494

cc_library(
    name = "cpp",
    hdrs = [":include"],
    visibility = ["//visibility:public"],
    includes = [
        "include",
        "include/torch/csrc/api/include",
        "include/TH",
        "include/THC",
    ],
    deps = [
        "@//third_party/python:headers",
    ]
)