mehrdadh commented on a change in pull request #8715:
URL: https://github.com/apache/tvm/pull/8715#discussion_r688010083
##########
File path: tests/python/unittest/test_crt.py
##########
@@ -219,5 +219,109 @@ def test_platform_timer():
assert len(result.results) == 3
[email protected]_micro
+def test_autotune():
+ """Verify that autotune works with micro."""
+
+ RELAY_MODEL = """
+#[version = "0.0.5"]
+def @main(%data : Tensor[(1, 3, 64, 64), uint8], %weight : Tensor[(8, 3, 5,
5), int8]) {
+ %1 = nn.conv2d(
+ %data,
+ %weight,
+ padding=[2, 2],
+ channels=8,
+ kernel_size=[5, 5],
+ data_layout="NCHW",
+ kernel_layout="OIHW",
+ out_dtype="int32");
+ %1
+}
+"""
+ mod = tvm.parser.fromtext(RELAY_MODEL)
Review comment:
done.
##########
File path: tests/micro/zephyr/test_zephyr.py
##########
@@ -400,5 +396,137 @@ def test_tensors(sess):
test_tensors(sess)
+def _get_conv2d_model(input_shape: tuple):
+ """Build a conv2d operator in Keras and returns an (IRModule,
parameters)"""
+ import tensorflow as tf
+ from tensorflow import keras
+
+ model = keras.models.Sequential()
+ model.add(keras.layers.Conv2D(2, 3, input_shape=input_shape))
+ model.build()
+
+ inputs = {
+ i.name.split(":", 2)[0]: [x if x is not None else 1 for x in
i.shape.as_list()]
+ for i in model.inputs
+ }
+ inputs = {k: [v[0], v[3], v[1], v[2]] for k, v in inputs.items()}
+ mod, params = relay.frontend.from_keras(model, inputs, layout="NCHW")
+ return mod, params
+
+
[email protected]_micro
+def test_autotune_conv2d(temp_dir, platform, west_cmd, tvm_debug):
+ """Test AutoTune for microTVM Zephyr"""
+ model, zephyr_board = PLATFORMS[platform]
+
+ sample = np.random.rand(1, 3, 16, 16)
+ mod, params = _get_conv2d_model((16, 16, 3))
+
+ target = tvm.target.target.micro(model)
+ pass_context = tvm.transform.PassContext(opt_level=3,
config={"tir.disable_vectorize": True})
+ with pass_context:
+ tasks = tvm.autotvm.task.extract_from_program(mod["main"], {}, target)
+ assert len(tasks) > 0
+
+ repo_root = pathlib.Path(
+ subprocess.check_output(["git", "rev-parse", "--show-toplevel"],
encoding="utf-8").strip()
+ )
+ module_loader = tvm.micro.autotvm_module_loader(
+ template_project_dir=repo_root / "apps" / "microtvm" / "zephyr" /
"template_project",
+ project_options={
+ "zephyr_board": zephyr_board,
+ "west_cmd": west_cmd,
+ "verbose": 1,
+ "project_type": "host_driven",
+ },
+ )
+ builder = tvm.autotvm.LocalBuilder(
+ n_parallel=1,
+ build_kwargs={"build_option": {"tir.disable_vectorize": True}},
+ do_fork=False,
+ build_func=tvm.micro.autotvm_build_func,
+ ) # do_fork=False needed to persist stateful builder.
+ runner = tvm.autotvm.LocalRunner(number=1, repeat=1, timeout=0,
module_loader=module_loader)
+
+ measure_option = tvm.autotvm.measure_option(builder=builder, runner=runner)
+
+ log_path = pathlib.Path("zephyr_autotune.log")
+ if log_path.exists():
+ log_path.unlink()
+
+ n_trial = 10
+ for task in tasks:
+ print(f"mehrdad: {task}")
Review comment:
done.
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