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#
# http://www.apache.org/licenses/LICENSE-2.0
#
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import numpy as np
import platform
import pytest
import re
import textwrap
import tvm
from tvm import te
llvm_version = tvm.target.codegen.llvm_version_major()
machine = platform.machine()
if machine not in ["i386", "x86_64", "AMD64", "amd64"]:
pytest.skip(f"Requires x86_64/i386, but machine is {machine}", allow_module_level=True)
@tvm.testing.requires_llvm
@pytest.mark.skipif(llvm_version < 6, reason=f"Requires LLVM 6+, got {llvm_version}")
def test_fp16_to_fp32():
def fp16_to_fp32(target, width, match=None, not_match=None):
elements = 64
n = tvm.runtime.convert(elements)
A = te.placeholder((n, width), dtype="float16", name="A")
B = te.compute(A.shape, lambda *i: A(*i).astype("float32"), name="B")
s = te.create_schedule(B.op)
s[B].vectorize(s[B].op.axis[1])
f = tvm.build(s, [A, B], target)
assembly = f.get_source("asm").splitlines()
if match:
matches = [l for l in assembly if re.search(match, l)]
assert matches
if not_match:
not_matches = [l for l in assembly if re.search(not_match, l)]
assert not not_matches
fp16_to_fp32("llvm -mcpu=skylake-avx512", 15, match="vcvtph2ps.*mm")
fp16_to_fp32("llvm -mcpu=skylake-avx512", 16, match="vcvtph2ps.*mm")
fp16_to_fp32("llvm -mcpu=skylake-avx512", 17, match="vcvtph2ps.*mm")
fp16_to_fp32("llvm -mcpu=skylake-avx512", 49, match="vcvtph2ps.*mm")
fp16_to_fp32("llvm -mcpu=skylake-avx512 -mattr=-avx512f", 49, match="vcvtph2ps.*mm")
fp16_to_fp32("llvm -mcpu=skylake-avx512 -mattr=-f16c,-avx512f", 49, not_match="vcvtph2ps")
fp16_to_fp32("llvm -mcpu=core-avx2", 8, match="vcvtph2ps.*mm")
fp16_to_fp32("llvm -mcpu=core-avx2", 9, match="vcvtph2ps.*mm")
fp16_to_fp32("llvm", 9, not_match="vcvtph2ps")
is_32bit = platform.architecture()[0] == "32bit"
@tvm.testing.requires_llvm
@pytest.mark.skipif(is_32bit, reason=f"Fails in CI due to architecture mismatch in JIT")
@pytest.mark.parametrize("feature_string", ["-sse2", "+sse2"])
def test_fp16_fp32_conversions(feature_string):
relay_model = textwrap.dedent(
"""
#[version = "0.0.5"]
def @main(%inp : Tensor[(3), float32], %cst : Tensor[(3), float32]) {
%1 = cast(%inp, dtype="float16");
%2 = cast(%cst, dtype="float16");
%3 = add(%1, %2);
%4 = cast(%3, dtype="float32");
%4
}
"""
)
ir_mod = tvm.relay.fromtext(relay_model)
arch = "i386" if machine == "i386" else "x86_64"
aot_factory = tvm.relay.build(
ir_mod,
params={"cst": np.array([1.0, 2.0, 3.0], dtype="float32")},
target=f"llvm --mtriple={arch} --mattr={feature_string}",
executor=tvm.relay.backend.Executor(
"aot", {"interface-api": "packed", "unpacked-api": False}
),
)
mod_name = aot_factory["list_module_names"]()[0]
executor = aot_factory[mod_name]
mod = executor(tvm.cpu(0))
inp = tvm.nd.array(np.array([1.1, 2.1, 3.1], dtype="float32"), device=tvm.cpu(0))
mod.get_function("set_input")(0, inp)
mod.get_function("run")()
out = mod.get_function("get_output")(0)
expected = np.array([2.1, 4.1, 6.1], dtype="float32")
np.testing.assert_allclose(out.asnumpy(), expected, rtol=1e-3)
if __name__ == "__main__":
test_fp16_to_fp32()