def build_and_eval(lib, s, bufs, target, dev_id, rpc_info: RpcInfo = None, number=1):
if rpc_info is not None:
target_host = rpc_info.target_host
fcompile = rpc_info.fcompile
use_rpc = rpc_info.use_rpc
else:
target_host, fcompile, use_rpc = None, None, None
# mod = tvm.lower(s, bufs, simple_mode=True)
# print("Building...")
func = tvm.build(s, bufs, target=target, target_host=target_host)
tvm_arys = []
try:
func.export_library(lib, fcompile)
# print("Connecting...")
remote = rpc_info.get_remote()
# print("Allocating...")
ctx = (remote if remote else tvm).device(target, dev_id)
for buf in bufs:
shape = to_tuple(buf.shape)
tmp = np.random.uniform(0, 1, size=shape).astype(buf.dtype)
tmp = tvm.nd.array(tmp, ctx)
tvm_arys.append(tmp)
if use_rpc:
# print("Uploading...")
remote.upload(lib)
func = remote.load_module(os.path.split(lib)[-1])
else:
func = tvm.runtime.module.load_module(lib)
# print("Evaluating...")
evaluator = func.time_evaluator(func.entry_name, ctx, number=number)
time_cost = evaluator(*tvm_arys).mean * 1e3
finally:
while len(tvm_arys) > 0:
del tvm_arys[-1]
return time_cost
if __name__ == "__main__":
N, C, H, W, K, _, k, _, _, st, pad, dilation, group = yolo_shapes_b1[5]
use_bias = False
vlen = 8
target = "llvm"
dev_id = 0
trials = 100
timeout = 10
parallel = 20
method = "searching"
force_inline = True
use_model = False
logfile = open("tmp.log", "w")
rpc_info = RpcInfo("0.0.0.0", 9090, target_host="llvm")
args = (N, C, H, W, K, k, use_bias, st, pad, dilation, group)
task = Task("conv2d_nchwc",
"yolo_conv6",
conv2d_nchwc_compute_avx2,
args,
target,
dev_id=dev_id)
register_task(task, override=False)
beg = time.time()
s, bufs, configs = schedule(task.key,
op_trial=trials,
timeout=timeout,
op_stop=30,
parser.add_argument("--timeout", help="timeout", type=float, default=4.0)
parser.add_argument("--parallel", help="parallel", type=int, default=1)
parser.add_argument("--use_model",
help="use performance model",
action="store_true")
parser.add_argument("--method",
help="how to schedule",
type=str,
default="searching")
parser.add_argument("--host", type=str, default="0.0.0.0")
parser.add_argument("--target_host", type=str, default="llvm")
parser.add_argument("--port", type=int, default=9090)
parser.add_argument("--force_inline", action="store_true")
# parser.add_argument("--op_hint", type=str, default="split_fuse")
args = parser.parse_args()
rpc_info = RpcInfo(args.host, args.port, target_host=args.target_host)
shapes = PixelCNN_shape
if args.to < 0:
end = len(shapes)
else:
end = args.to
if args.log != "":
with open(args.log, "a") as flog:
ret = optimize(
args.shapes,
args.from_,
shapes[args.from_:end],
target=args.target,
dev_id=args.device,
timeout=args.timeout,
line = task.key + ":" + string
print(line, file=logfile, flush=True)
s, bufs = schedule_with_config(task.key, configs)
time_cost = evaluate(task.key, s, bufs, target, task.dev_id, 10,
rpc_info)
print("Use", time_cost, "ms")
print("Cost", end - beg, "s")
print()
return ret
if __name__ == "__main__":
parser = argparse.ArgumentParser()
init_arg_parser(parser)
args = parser.parse_args()
rpc_info = RpcInfo(args.host, args.port, args.target_host, args.device_key,
args.use_rpc, args.fcompile, args.timeout)
shapes = conv1d_shapes
if args.to < 0:
end = len(shapes)
else:
end = args.to
if args.test != "":
with open(args.test, "r") as fin:
for line in fin:
name, string = line.split(":", 1)
obj = json.loads(string)
configs = Config(obj[0], obj[1])
test(name, configs, args.device, rpc_info, args.check)
