apps/benchmark/util.py

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"""Utility for benchmark"""

import sys
from tvm import relay
from tvm.relay import testing


def get_network(name, batch_size, dtype="float32"):
    """Get the symbol definition and random weight of a network

    Parameters
    ----------
    name: str
        The name of the network, can be 'resnet-18', 'resnet-50', 'vgg-16', 'inception_v3', 'mobilenet', ...
    batch_size: int
        batch size
    dtype: str
        Data type

    Returns
    -------
    net: tvm.IRModule
        The relay function of network definition
    params: dict
        The random parameters for benchmark
    input_shape: tuple
        The shape of input tensor
    output_shape: tuple
        The shape of output tensor
    """
    input_shape = (batch_size, 3, 224, 224)
    output_shape = (batch_size, 1000)

    if name == "mobilenet":
        net, params = testing.mobilenet.get_workload(batch_size=batch_size, dtype=dtype)
    elif name == "inception_v3":
        input_shape = (batch_size, 3, 299, 299)
        net, params = testing.inception_v3.get_workload(batch_size=batch_size, dtype=dtype)
    elif "resnet" in name:
        n_layer = int(name.split("-")[1])
        net, params = testing.resnet.get_workload(
            num_layers=n_layer, batch_size=batch_size, dtype=dtype
        )
    elif "vgg" in name:
        n_layer = int(name.split("-")[1])
        net, params = testing.vgg.get_workload(
            num_layers=n_layer, batch_size=batch_size, dtype=dtype
        )
    elif "densenet" in name:
        n_layer = int(name.split("-")[1])
        net, params = testing.densenet.get_workload(
            densenet_size=n_layer, batch_size=batch_size, dtype=dtype
        )
    elif "squeezenet" in name:
        version = name.split("_v")[1]
        net, params = testing.squeezenet.get_workload(
            batch_size=batch_size, version=version, dtype=dtype
        )
    elif name == "mxnet":
        # an example for mxnet model
        from mxnet.gluon.model_zoo.vision import get_model

        block = get_model("resnet18_v1", pretrained=True)
        net, params = relay.frontend.from_mxnet(block, shape={"data": input_shape}, dtype=dtype)
        net = net["main"]
        net = relay.Function(
            net.params, relay.nn.softmax(net.body), None, net.type_params, net.attrs
        )
        net = tvm.IRModule.from_expr(net)
    else:
        raise ValueError("Unsupported network: " + name)

    return net, params, input_shape, output_shape


def print_progress(msg):
    """print progress message

    Parameters
    ----------
    msg: str
        The message to print
    """
    sys.stdout.write(msg + "\r")
    sys.stdout.flush()