| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| import tvm |
| from tvm import te |
| import re |
| import os |
| import ctypes |
| |
| |
| def test_popcount(): |
| target = "llvm -mtriple=armv7l-none-linux-gnueabihf -mcpu=cortex-a53 -mattr=+neon" |
| |
| def check_correct_assembly(type, elements, counts): |
| n = tvm.runtime.convert(elements) |
| A = te.placeholder(n, dtype=type, name="A") |
| B = te.compute(A.shape, lambda i: tvm.tir.popcount(A[i]), name="B") |
| s = te.create_schedule(B.op) |
| s[B].vectorize(s[B].op.axis[0]) |
| f = tvm.build(s, [A, B], target) |
| |
| # Verify we see the correct number of vpaddl and vcnt instructions in the assembly |
| assembly = f.get_source("asm") |
| matches = re.findall("vpaddl", assembly) |
| assert len(matches) == counts |
| matches = re.findall("vcnt", assembly) |
| assert len(matches) == 1 |
| |
| check_correct_assembly("uint16", 8, 1) |
| check_correct_assembly("uint16", 4, 1) |
| check_correct_assembly("uint32", 4, 2) |
| check_correct_assembly("uint32", 2, 2) |
| check_correct_assembly("uint64", 2, 3) |
| |
| |
| def test_vmlal_s16(): |
| target = "llvm -mtriple=armv7l-none-linux-gnueabihf -mcpu=cortex-a53 -mattr=+neon" |
| |
| def check_correct_assembly(N): |
| K = te.size_var("K") |
| A = te.placeholder((K, N), dtype="int8", name="A") |
| B = te.placeholder((K, N), dtype="int8", name="B") |
| k = te.reduce_axis((0, K)) |
| C = te.compute( |
| (N,), |
| lambda n: te.sum(A[k, n].astype("int32") * B[k, n].astype("int32"), axis=[k]), |
| name="C", |
| ) |
| s = te.create_schedule(C.op) |
| s[C].vectorize(s[C].op.axis[0]) |
| f = tvm.build(s, [A, B, C], target) |
| |
| # Verify we see the correct number of vmlal.s16 instructions |
| assembly = f.get_source("asm") |
| matches = re.findall("vmlal.s16", assembly) |
| assert len(matches) == N // 4 |
| |
| check_correct_assembly(8) |
| check_correct_assembly(16) |
| check_correct_assembly(32) |
| check_correct_assembly(64) |
| |
| def check_broadcast_correct_assembly(N): |
| K = te.size_var("K") |
| A = te.placeholder((K, N), dtype="int8", name="A") |
| B = te.placeholder((K,), dtype="int8", name="B") |
| k = te.reduce_axis((0, K)) |
| C = te.compute( |
| (N,), |
| lambda n: te.sum(A[k, n].astype("int32") * B[k].astype("int32"), axis=[k]), |
| name="C", |
| ) |
| s = te.create_schedule(C.op) |
| s[C].vectorize(s[C].op.axis[0]) |
| f = tvm.build(s, [A, B, C], target) |
| |
| # Verify we see the correct number of vmlal.s16 instructions |
| assembly = f.get_source("asm") |
| matches = re.findall("vmlal.s16", assembly) |
| assert len(matches) == N // 4 |
| |
| check_broadcast_correct_assembly(8) |
| check_broadcast_correct_assembly(16) |
| check_broadcast_correct_assembly(32) |
| check_broadcast_correct_assembly(64) |
| |
| |
| if __name__ == "__main__": |
| test_popcount() |
| test_vmlal_s16() |