relay_integration.py

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# pylint: disable=unused-variable,invalid-name
"""
Decorator and utilities for the integration with TOPI and Relay
99.9% copy-paste of implementation by @MerryMercy

"""
import threading
import warnings
import logging


from .task import create
from .topi_integration import TaskExtractEnv

logger = logging.getLogger('autotvm')


# TODO(moreau89) find a more elegant way to build for VTAs
def _build(func,
           target,
           target_host,
           params):
    """ Helper to build VTA properly.
    """

    from tvm import relay

    if hasattr(target, 'device_name') and target.device_name == "vta":
        with relay.build_config(opt_level=3, disabled_pass={"AlterOpLayout"}):
            import vta
            with vta.build_config():
                return relay.build(func, target, target_host, params)
    # default case
    return relay.build(func, target, target_host, params)

def extract_from_program(func, params, ops, target, target_host=None):
    """ Extract tuning tasks from a relay program.

    This function collects tuning tasks by building the program
    with a "tracing" target and tracing all the calls to topi.

    Parameters
    ----------
    func: relay.expr.Function
        The func to tune
    params: dict of str to numpy array
        The associated parameters of the program
    ops: List of relay op
        List of relay ops to be tuned
    target: tvm.target.Target
        The compilation target
    target_host: tvm.target.Target
        The host compilation target

    Returns
    -------
    task: Array of autotvm.task.Task
        collected tasks
    """
    import tvm.relay.op
    from tvm import relay
    import topi

    env = TaskExtractEnv.get()

    # NOTE: To add more ops, you only need to change the following lists
    # relay op -> topi compute
    OP2TOPI = {
        tvm.relay.op.nn.conv2d: [topi.nn.conv2d, topi.nn.depthwise_conv2d_nchw,
                                 topi.nn.group_conv2d_nchw, topi.nn.conv2d_NCHWc],
        tvm.relay.op.nn.conv2d_transpose: [topi.nn.conv2d_transpose_nchw],
        tvm.relay.op.nn.dense: [topi.nn.dense],
        tvm.relay.op.nn.deformable_conv2d: [topi.nn.deformable_conv2d_nchw],
    }

    topi_funcs = []
    for op_name in ops:
        if op_name in OP2TOPI:
            topi_funcs.extend(OP2TOPI[op_name])
        else:
            warnings.warn("Op %s is not tunable, ignored" % op_name)

    # run compiler to collect all TOPI calls during compilation
    env.reset(topi_funcs)
    with env:
        # disable logger temporarily
        old_state = logger.disabled
        logger.disabled = True

        relay.backend.compile_engine.get().clear()
        # wrap build call in thread to avoid multiprocessing problems
        mod = relay.Module.from_expr(func)
        build_thread = threading.Thread(target=_build,
                                        args=(mod,
                                              target,
                                              target_host,
                                              params))
        build_thread.start()
        build_thread.join()

        logger.disabled = old_state

    # create tasks for target
    tasks = []
    for task_name, args in env.get_tasks():
        try:
            tsk = create(task_name, args,
                         target=target, target_host=target_host,
                         template_key='direct')
            tasks.append(tsk)
        except topi.InvalidShapeError:
            warnings.warn("Invalid shape during AutoTVM task creation")
    return tasks


def extract_from_multiple_program(funcs, params, ops, target, target_host=None):
    """ Extract tuning tasks from multiple relay programs.

    This function is the multiple program version of extract_from_program

    Parameters
    ----------
    funcs: List of relay.expr.Function
        The list of functions to tune
    params: List of dict of str to numpy array
        The associated parameters of the programs
    ops: List of relay op
        List of relay ops to be tuned
    target: tvm.target.Target
        The compilation target
    target_host: tvm.target.Target
        The host compilation target

    Returns
    -------
    task: Array of autotvm.task.Task
        collected tasks
    """
    env = TaskExtractEnv.get()
    import tvm.relay.op
    from tvm import relay
    import topi

    # NOTE: To add more ops, you only need to change the following lists
    # relay op -> topi compute
    OP2TOPI = {
        tvm.relay.op.nn.conv2d: [topi.nn.conv2d, topi.nn.depthwise_conv2d_nchw,
                                 topi.nn.group_conv2d_nchw],
        tvm.relay.op.nn.conv2d_transpose: [topi.nn.conv2d_transpose_nchw],
        tvm.relay.op.nn.dense: [topi.nn.dense],
        tvm.relay.op.nn.contrib_deformable_conv2d: [topi.nn.deformable_conv2d_nchw],
    }

    topi_funcs = []
    for op_name in ops:
        if op_name in OP2TOPI:
            topi_funcs.extend(OP2TOPI[op_name])
        else:
            warnings.warn("Op %s is not tunable, ignored" % op_name)

    # run compiler to collect all TOPI calls during compilation
    env.reset(topi_funcs)
    with env:
        # disable logger temporarily
        old_state = logger.disabled
        logger.disabled = True

        for func, param in zip(funcs, params):
            relay.backend.compile_engine.get().clear()
            # wrap build call in thread to avoid multiprocessing problems
            mod = relay.Module.from_expr(func)
            build_thread = threading.Thread(target=my_build,
                                            args=(mod,
                                                  target,
                                                  target_host,
                                                  params))
            build_thread.start()
            build_thread.join()

        logger.disabled = old_state

    # create tasks for target
    tasks = []
    for task_name, args in env.get_tasks():
        try:
            tsk = create(task_name, args,
                         target=target, target_host=target_host,
                         template_key='direct')
            tasks.append(tsk)
        except topi.InvalidShapeError:
            print("[Warning] Invalid shape during AutoTVM task creation")

    return tasks