Update py_import macros for the ability to unpack additional wheels in the same folder as the main wheel.

[copybara-service]

Update py_import macros for the ability to unpack additional wheels in the same folder as the main wheel.

Usage example: provide NVIDIA wheel dependencies for ML wheels that have rpaths pointing to NVIDIA folders. When a user executes pip install tensorflow[and_cuda], NVIDIA wheels are installed together with Tensorflow wheel. To reproduce this behavior in hermetic Python approach, we need to define py_import as follows (provided NVIDIA dependencies are defined in requirements.in and requirements lock files):

    py_import(
        name = "tf_py_import",
        wheel = ":wheel",
        deps = [
            "@pypi_absl_py//:pkg",
            "@pypi_astunparse//:pkg",
            "@pypi_flatbuffers//:pkg",
            "@pypi_gast//:pkg",
            "@pypi_ml_dtypes//:pkg",
            "@pypi_numpy//:pkg",
            "@pypi_opt_einsum//:pkg",
            "@pypi_packaging//:pkg",
            "@pypi_protobuf//:pkg",
            "@pypi_requests//:pkg",
            "@pypi_termcolor//:pkg",
            "@pypi_typing_extensions//:pkg",
            "@pypi_wrapt//:pkg",
        ],
        wheel_deps = [
            "@pypi_nvidia_cublas_cu12//:whl",
            "@pypi_nvidia_cuda_cupti_cu12//:whl",
            "@pypi_nvidia_cuda_nvcc_cu12//:whl",
            "@pypi_nvidia_cuda_nvrtc_cu12//:whl",
            "@pypi_nvidia_cuda_runtime_cu12//:whl",
            "@pypi_nvidia_cudnn_cu12//:whl",
            "@pypi_nvidia_cufft_cu12//:whl",
            "@pypi_nvidia_curand_cu12//:whl",
            "@pypi_nvidia_cusolver_cu12//:whl",
            "@pypi_nvidia_cusparse_cu12//:whl",
            "@pypi_nvidia_nccl_cu12//:whl",
            "@pypi_nvidia_nvjitlink_cu12//:whl",
        ],
    )