ekalda commented on code in PR #15069:
URL: https://github.com/apache/tvm/pull/15069#discussion_r1235232441
##########
tests/python/contrib/test_ethosu/test_legalize.py:
##########
@@ -3526,20 +3528,72 @@ def representative_dataset():
assert tuple(func_body.args[1].checked_type.shape) == (256,)
[email protected]("ifm_shape", [(1, 12), (1, 12, 32)])
-def test_tflite_softmax(ifm_shape):
+def test_tflite_softmax():
+ np.random.seed(0)
dtype = "int8"
+ ifm_shape = (1, 12)
+
+ def get_expected_mod():
+ # fmt: off
+ mod_str = """
+ #[version = "0.0.5"]
+ def @main(%x: Tensor[(1, 12), int8] /* ty=Tensor[(1, 12), int8]
span=x:0:0 */, output_tensor_names=["Identity"]) -> Tensor[(1, 12), int8] {
+ @tvmgen_default_ethos_u_main_0(%x) /* ty=Tensor[(1, 12), int8] */
+ }
+
+ def @tvmgen_default_ethos_u_main_0(%y: Tensor[(1, 12), int8] /*
ty=Tensor[(1, 12), int8] */, Compiler="ethos-u", Primitive=1, Inline=1,
global_symbol="tvmgen_default_ethos_u_main_0") -> Tensor[(1, 12), int8] {
+ %0 = reshape(%y, newshape=[1, 1, 12, 1]);
+ %1 = reshape(%0, newshape=[1, 1, 1, 12]);
+ %2 = contrib.ethosu.pooling(%0, meta[relay.Constant][0],
pooling_type="MAX", ifm_scale=0.011756030842661858f, ifm_zero_point=-43,
ofm_scale=0f, ofm_zero_point=-43, pool_shape=[1, 12], ofm_channels=1,
ofm_dtype="int8");
+ %3 = contrib.ethosu.binary_elementwise(%1, %2,
meta[relay.Constant][1], operator_type="SUB", ifm_scale=0.011756030842661858f,
ifm_zero_point=-43, ifm2_scale=0f, ifm2_zero_point=-43, ofm_scale=1f,
ofm_zero_point=127, ifm_channels=12, ifm2_channels=1, activation="LUT",
clip_min=-255, clip_max=0, ofm_dtype="int32");
+ %4 = contrib.ethosu.binary_elementwise(%3,
meta[relay.Constant][2], meta[relay.Constant][0], operator_type="SHR",
ifm_scale=1f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, ifm_channels=12, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, rounding_mode="NATURAL", ofm_dtype="int32");
+ %5 = contrib.ethosu.pooling(%4, meta[relay.Constant][0],
pooling_type="SUM", ifm_scale=0f, ifm_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, pool_shape=[1, 1], ofm_channels=1, ofm_dtype="int32",
activation="CLIP", clip_min=-128, clip_max=127);
+ %6 = contrib.ethosu.unary_elementwise(%5, meta[relay.Constant][0],
operator_type="CLZ", ifm_scale=0f, ifm_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, ofm_channels=1, activation="CLIP", clip_min=-128,
clip_max=127);
+ %7 = contrib.ethosu.binary_elementwise(%6,
meta[relay.Constant][3], meta[relay.Constant][0], operator_type="SUB",
ifm_scale=0f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %8 = contrib.ethosu.binary_elementwise(%5, %7,
meta[relay.Constant][0], operator_type="SHL", ifm_scale=0f, ifm_zero_point=0,
ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0f, ofm_zero_point=-43,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %9 = contrib.ethosu.binary_elementwise(%8,
meta[relay.Constant][4], meta[relay.Constant][0], operator_type="SUB",
ifm_scale=0f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %10 = contrib.ethosu.binary_elementwise(%9,
meta[relay.Constant][3], meta[relay.Constant][0], operator_type="SHL",
ifm_scale=0f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %11 = contrib.ethosu.binary_elementwise(%10,
meta[relay.Constant][5], meta[relay.Constant][0], operator_type="ADD",
ifm_scale=0f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=1f,
ofm_zero_point=0, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32", use_rescale=True,
rescale_scale=1, rescale_shift=1);
+ %12 = contrib.ethosu.binary_elementwise(%11,
meta[relay.Constant][6], meta[relay.Constant][0], operator_type="MUL",
ifm_scale=1f, ifm_zero_point=0, ifm2_scale=1f, ifm2_zero_point=0, ofm_scale=2f,
ofm_zero_point=0, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %13 = contrib.ethosu.binary_elementwise(%12,
meta[relay.Constant][7], meta[relay.Constant][0], operator_type="ADD",
ifm_scale=2f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=1f,
ofm_zero_point=0, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %14 = contrib.ethosu.binary_elementwise(%13, %11,
meta[relay.Constant][0], operator_type="MUL", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=1f, ifm2_zero_point=0, ofm_scale=2f, ofm_zero_point=0,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %15 = contrib.ethosu.binary_elementwise(meta[relay.Constant][8],
%14, meta[relay.Constant][0], operator_type="SUB", ifm_scale=2f,
ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=1f,
ofm_zero_point=0, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %16 = contrib.ethosu.binary_elementwise(%13, %15,
meta[relay.Constant][0], operator_type="MUL", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=1f, ifm2_zero_point=0, ofm_scale=2f, ofm_zero_point=0,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %17 = contrib.ethosu.binary_elementwise(%16,
meta[relay.Constant][9], meta[relay.Constant][0], operator_type="MUL",
ifm_scale=2f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %18 = contrib.ethosu.binary_elementwise(%13, %17,
meta[relay.Constant][0], operator_type="ADD", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=1f, ofm_zero_point=0,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %19 = contrib.ethosu.binary_elementwise(%18, %11,
meta[relay.Constant][0], operator_type="MUL", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=1f, ifm2_zero_point=0, ofm_scale=2f, ofm_zero_point=0,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %20 = contrib.ethosu.binary_elementwise(meta[relay.Constant][8],
%19, meta[relay.Constant][0], operator_type="SUB", ifm_scale=2f,
ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=1f,
ofm_zero_point=0, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %21 = contrib.ethosu.binary_elementwise(%18, %20,
meta[relay.Constant][0], operator_type="MUL", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=1f, ifm2_zero_point=0, ofm_scale=2f, ofm_zero_point=0,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %22 = contrib.ethosu.binary_elementwise(%21,
meta[relay.Constant][9], meta[relay.Constant][0], operator_type="MUL",
ifm_scale=2f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %23 = contrib.ethosu.binary_elementwise(%18, %22,
meta[relay.Constant][0], operator_type="ADD", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=1f, ofm_zero_point=0,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %24 = contrib.ethosu.binary_elementwise(%23, %11,
meta[relay.Constant][0], operator_type="MUL", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=1f, ifm2_zero_point=0, ofm_scale=2f, ofm_zero_point=0,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %25 = contrib.ethosu.binary_elementwise(meta[relay.Constant][8],
%24, meta[relay.Constant][0], operator_type="SUB", ifm_scale=2f,
ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=1f,
ofm_zero_point=0, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %26 = contrib.ethosu.binary_elementwise(%23, %25,
meta[relay.Constant][0], operator_type="MUL", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=1f, ifm2_zero_point=0, ofm_scale=2f, ofm_zero_point=0,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %27 = contrib.ethosu.binary_elementwise(%26,
meta[relay.Constant][9], meta[relay.Constant][0], operator_type="MUL",
ifm_scale=2f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %28 = contrib.ethosu.binary_elementwise(%23, %27,
meta[relay.Constant][0], operator_type="ADD", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=1f, ofm_zero_point=0,
ifm_channels=1, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %29 = contrib.ethosu.binary_elementwise(%28,
meta[relay.Constant][10], meta[relay.Constant][0], operator_type="MUL",
ifm_scale=1f, ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=1f,
ofm_zero_point=0, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %30 = contrib.ethosu.binary_elementwise(%3, %29,
meta[relay.Constant][0], operator_type="MUL", ifm_scale=1f, ifm_zero_point=0,
ifm2_scale=1f, ifm2_zero_point=0, ofm_scale=2f, ofm_zero_point=0,
ifm_channels=12, ifm2_channels=1, activation="CLIP", clip_min=-128,
clip_max=127, ofm_dtype="int32");
+ %31 = contrib.ethosu.binary_elementwise(meta[relay.Constant][11],
%6, meta[relay.Constant][0], operator_type="SUB", ifm_scale=0f,
ifm_zero_point=0, ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0f,
ofm_zero_point=-43, ifm_channels=1, ifm2_channels=1, activation="CLIP",
clip_min=-128, clip_max=127, ofm_dtype="int32");
+ %32 = contrib.ethosu.binary_elementwise(%30, %31,
meta[relay.Constant][0], operator_type="SHR", ifm_scale=2f, ifm_zero_point=0,
ifm2_scale=0f, ifm2_zero_point=0, ofm_scale=0.00390625f, ofm_zero_point=-128,
ifm_channels=12, ifm2_channels=1, rounding_mode="NATURAL", ofm_dtype="int8");
+ reshape(%32, newshape=[1, 12])
+ }
+
+ #[metadata]{ "root": 1, "nodes": [ { "type_key": "" },
{ "type_key": "Map", "keys": [ "relay.Constant" ],
"data": [2] }, { "type_key": "Array", "data": [ 3,
6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16 ] }, {
"type_key": "relay.Constant", "attrs": { "_checked_type_": "0",
"data": "0", "span": "0", "virtual_device_": "4" }
}, { "type_key": "VirtualDevice", "attrs": {
"device_type_int": "-1", "memory_scope": "5", "target": "0",
"virtual_device_id": "-1" } }, { "type_key":
"runtime.String" }, { "type_key": "relay.Constant", "attrs":
{ "_checked_type_": "0", "data": "1", "span": "0",
"virtual_device_": "4" } }, { "type_key": "relay.Constant
", "attrs": { "_checked_type_": "0", "data": "2",
"span": "0", "virtual_device_": "4" } }, { "type_key":
"relay.Constant", "attrs": { "_checked_type_": "0",
"data": "3", "span": "0", "virtual_device_": "4" } },
{ "type_key": "relay.Constant", "attrs": {
"_checked_type_": "0", "data": "4", "span": "0",
"virtual_device_": "4" } }, { "type_key": "relay.Constant",
"attrs": { "_checked_type_": "0", "data": "5",
"span": "0", "virtual_device_": "4" } }, { "type_key":
"relay.Constant", "attrs": { "_checked_type_": "0",
"data": "6", "span": "0", "virtual_device_": "4" } },
{ "type_key": "relay.Constant", "attrs": {
"_checked_type_": "0", "data": "7", "span": "0",
"virtual_device_": "4"
} }, { "type_key": "relay.Constant", "attrs": {
"_checked_type_": "0", "data": "8", "span": "0",
"virtual_device_": "4" } }, { "type_key": "relay.Constant",
"attrs": { "_checked_type_": "0", "data": "9",
"span": "0", "virtual_device_": "4" } }, { "type_key":
"relay.Constant", "attrs": { "_checked_type_": "0",
"data": "10", "span": "0", "virtual_device_": "4" } },
{ "type_key": "relay.Constant", "attrs": {
"_checked_type_": "0", "data": "11", "span": "0",
"virtual_device_": "4" } } ], "b64ndarrays": [
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAAAQAAAAAgAQAAAAAAAAAAAAAAAAAAAAAA",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAAAQAAAAAgAQAAAQAAAAAAAAAEAAAAAAAAOAljBu1edgYu74kGq7qdBhbCsQYmBsYGkIfaBg5H7wZcRQQHOIMZB2IBLwecwEQHq8FaB1gFcQdrjIcHsVeeB/hntQcRvswHzVrkBwI//AeHaxQIN+EsCDehRQjiq14I
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
zCYTkzmmDVNbVcfTg3XC0/KIvtPEkPtUGtA4lF5I9pS+/TUU7y90lTahtNVWVnXVmY+3ldQP+hYgWX1WX26BVvlRxlcYRcwXfoySl6NpGdfLnaIYAuyrGFvYtRiEpX/YyFOLmW/m2Bm6IiWZ2sg0GhWbQ1q33pOa1lUk2xBBdxtN5kob+IbeXBgmc1xpB0mc9y0gnRca+N1nk1Idz5osXj9xx56oXmQe3KKBn19B4F+////fw==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAQAAAAAAAAADAAAAA==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAQAAAAAAAAAAQAAAA==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAQAAAAAAAAAAAAAQA==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAQAAAAAAAAA////fw==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAQAAAAAAAAAxMPDww==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAQAAAAAAAAAWlpaWg==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAA
ABAAAAAAAAAAQAAAAAAAAAAAAAIA==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAQAAAAAAAAABAAAAA==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAQAAAAAAAAAAgAAAA==",
"P6G0lvBAXt0AAAAAAAAAAAEAAAAAAAAABAAAAAAgAQABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAAAQAAAAAAAAAIwAAAA=="
]}
Review Comment:
Hmm, I think testing against all that junk in metadata will be very fragile.
Did you discover the clipping problem when you run the softmax with input data
that differs from the input data we normally generate in the codegen tests? If
that is the case, I think you can keep the legalization test as it currently is
and add a codegen test with different representative data that before this
change was failing. If that's not possible to do, then I think it would be
better to check the attributes as we visit the graph, similarly how it checks
for the op type.
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