Function collect_env_info

tensorpack/tfutils/collect_env.py:39–119

Returns: str - a table contains important information about the environment

()

def collect_env_info():
    """
    Returns:
        str - a table contains important information about the environment
    """
    data = []
    data.append(("sys.platform", sys.platform))
    data.append(("Python", sys.version.replace("\n", "")))
    data.append(("Tensorpack", __git_version__ + " @" + os.path.dirname(tensorpack.__file__)))
    data.append(("Numpy", np.__version__))

    data.append(("TensorFlow", tfv1.VERSION + "/" + tfv1.GIT_VERSION + " @" + os.path.dirname(tf.__file__)))
    data.append(("TF Compiler Version", tfv1.COMPILER_VERSION))
    has_cuda = tf.test.is_built_with_cuda()
    data.append(("TF CUDA support", has_cuda))

    try:
        from tensorflow.python.framework import test_util
        data.append(("TF MKL support", test_util.IsMklEnabled()))
    except Exception:
        pass

    try:
        from tensorflow.python.framework import test_util
        data.append(("TF XLA support", test_util.is_xla_enabled()))
    except Exception:
        pass

    if has_cuda:
        data.append(("Nvidia Driver", find_library("nvidia-ml")))
        data.append(("CUDA libs", find_library("cudart")))
        data.append(("CUDNN libs", find_library("cudnn")))
        for k, v in parse_TF_build_info().items():
            data.append((k, v))
        data.append(("NCCL libs", find_library("nccl")))

        # List devices with NVML
        data.append(
            ("CUDA_VISIBLE_DEVICES",
             os.environ.get("CUDA_VISIBLE_DEVICES", "Unspecified")))
        try:
            devs = defaultdict(list)
            with NVMLContext() as ctx:
                for idx, dev in enumerate(ctx.devices()):
                    devs[dev.name()].append(str(idx))

            for devname, devids in devs.items():
                data.append(
                    ("GPU " + ",".join(devids), devname))
        except Exception:
            data.append(("GPU", "Not found with NVML"))

    vram = psutil.virtual_memory()
    data.append(("Free RAM", "{:.2f}/{:.2f} GB".format(vram.available / 1024**3, vram.total / 1024**3)))
    data.append(("CPU Count", psutil.cpu_count()))

    # Other important dependencies:
    try: