AndrewZhaoLuo commented on a change in pull request #10170:
URL: https://github.com/apache/tvm/pull/10170#discussion_r801057640
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File path: src/runtime/contrib/sort/sort.cc
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@@ -446,6 +446,20 @@
TVM_REGISTER_GLOBAL("tvm.contrib.sort.topk").set_body([](TVMArgs args, TVMRetVal
} else {
LOG(FATAL) << "Unsupported output dtype: " << out_dtype;
}
+ } else if (data_dtype == "int8") {
Review comment:
what about uint8 dtypes?
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File path: tests/python/relay/test_pass_fake_quantization_to_integer.py
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@@ -434,6 +434,21 @@ def test_fake_quantize_concat():
compare_fq_to_int(out, inputs_np)
[email protected]("k", [0, 1, 5])
[email protected]("axis", [0, -1, 1])
[email protected]("is_ascend", [True, False])
+def test_fake_quantize_topk(k, axis, is_ascend):
+ x = relay.var("x", shape=[20, 100], dtype="int8")
+ zero = relay.const(0)
+
+ x = relay.qnn.op.dequantize(x, relay.const(2.0), zero)
+ op = relay.topk(x, k, axis, "values", is_ascend, "float32")
+ op = relay.qnn.op.quantize(op, relay.const(2.0), zero, out_dtype="int8")
Review comment:
probably also want uint8
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