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#
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import logging
import os
import pathlib
import sys
import logging
import pytest
import numpy as np
import onnx
from PIL import Image
import tvm
import tvm.testing
import tvm.relay as relay
from tvm.relay.backend import Executor, Runtime
from tvm.relay.testing import byoc
from tvm.contrib import utils
from tvm.micro.testing.utils import check_tune_log
from tvm._ffi import get_global_func, register_func
import test_utils
def _make_session(temp_dir, zephyr_board, west_cmd, mod, build_config):
config_main_stack_size = None
if test_utils.qemu_boards(zephyr_board):
# fyi: qemu_riscv64 seems to be the greediest stack user
config_main_stack_size = 4096
else:
# increase stack size for HW platforms
config_main_stack_size = 2048
project_options = {
"project_type": "host_driven",
"west_cmd": west_cmd,
"verbose": bool(build_config.get("debug")),
"zephyr_board": zephyr_board,
}
if config_main_stack_size is not None:
project_options["config_main_stack_size"] = config_main_stack_size
project = tvm.micro.generate_project(
str(test_utils.TEMPLATE_PROJECT_DIR),
mod,
temp_dir / "project",
project_options,
)
project.build()
project.flash()
return tvm.micro.Session(project.transport())
@tvm.testing.requires_micro
@pytest.mark.skip_boards(["mps2_an521"])
def test_relay(temp_dir, board, west_cmd, tvm_debug):
"""Testing a simple relay graph"""
model = test_utils.ZEPHYR_BOARDS[board]
build_config = {"debug": tvm_debug}
shape = (10,)
dtype = "int8"
# Construct Relay program.
x = relay.var("x", relay.TensorType(shape=shape, dtype=dtype))
xx = relay.multiply(x, x)
z = relay.add(xx, relay.const(np.ones(shape=shape, dtype=dtype)))
func = relay.Function([x], z)
ir_mod = tvm.IRModule.from_expr(func)
runtime = Runtime("crt", {"system-lib": True})
executor = Executor("aot")
target = tvm.target.target.micro(model)
with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
mod = tvm.relay.build(ir_mod, target=target, runtime=runtime, executor=executor)
with _make_session(temp_dir, board, west_cmd, mod, build_config) as session:
aot_executor = tvm.runtime.executor.aot_executor.AotModule(session.create_aot_executor())
x_in = np.random.randint(10, size=shape[0], dtype=dtype)
aot_executor.run(x=x_in)
result = aot_executor.get_output(0).numpy()
tvm.testing.assert_allclose(aot_executor.get_input(0).numpy(), x_in)
tvm.testing.assert_allclose(result, x_in * x_in + 1)
@tvm.testing.requires_micro
@pytest.mark.skip_boards(["mps2_an521"])
def test_aot_executor(temp_dir, board, west_cmd, tvm_debug):
"""Test use of the AOT executor with microTVM."""
model = test_utils.ZEPHYR_BOARDS[board]
build_config = {"debug": tvm_debug}
shape = (10,)
dtype = "int8"
print("test_relay: construct relay program\n")
# Construct Relay program.
relay_mod = tvm.parser.fromtext(
"""
#[version = "0.0.5"]
def @main(%a : Tensor[(1, 2), uint8], %b : Tensor[(1, 2), uint8]) {
%0 = %a + %b;
%0
}"""
)
runtime = Runtime("crt", {"system-lib": True})
executor = Executor("aot")
target = tvm.target.target.micro(model)
with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
mod = tvm.relay.build(relay_mod, target=target, runtime=runtime, executor=executor)
def do_test():
aot_executor = tvm.runtime.executor.aot_executor.AotModule(session.create_aot_executor())
assert aot_executor.get_input_index("a") == 0
assert aot_executor.get_input_index("b") == 1
assert aot_executor.get_num_inputs() == 2
assert aot_executor.get_num_outputs() == 1
A_np = np.array([[2, 3]], dtype="uint8")
B_np = np.array([[4, 7]], dtype="uint8")
A_data = aot_executor.get_input("a").copyfrom(A_np)
B_data = aot_executor.get_input("b").copyfrom(B_np)
aot_executor.run()
out = aot_executor.get_output(0)
assert (out.numpy() == np.array([6, 10])).all()
B_np_new = np.array([[5, 8]])
aot_executor.set_input("b", B_np_new)
assert (B_data.numpy() == B_np_new).all()
with _make_session(temp_dir, board, west_cmd, mod, build_config) as session:
do_test()
if __name__ == "__main__":
tvm.testing.main()