chore: import upstream snapshot with attribution
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# ruff: noqa: F401, F821, F841
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import os
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import tempfile
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import numpy as np
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import pytest
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import tvm
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import tvm.testing
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from tvm import (
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DataType,
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IRModule,
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relax,
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tirx,
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)
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from tvm.relax.transform.legalize_ops import adreno as legalize_adreno
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from tvm.rpc import connect_tracker
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from tvm.script import ir as I
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from tvm.script import tirx as T
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from tvm.support import ndk
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from tvm.target import Target
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from tvm.testing import env
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def get_rpc():
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"""
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Establish an RPC connection to the remote device.
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Returns
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-------
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tvm.rpc.RPCSession or None
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The RPC session object if RPC_TARGET is set; otherwise, None.
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"""
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rpc_target = os.getenv("RPC_TARGET", None)
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if rpc_target:
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host = os.getenv("TVM_TRACKER_HOST", "localhost")
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port = int(os.getenv("TVM_TRACKER_PORT", 9090))
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device_key = os.getenv("RPC_DEVICE_KEY", "android")
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tracker = connect_tracker(host, port)
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return tracker.request(device_key, priority=1, session_timeout=1000)
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else:
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return None
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def preprocess_pipeline(mod: IRModule) -> IRModule:
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desired_layouts = {"relax.nn.conv2d": ["NCHW16c", "OIHW16o", "NCHW16c"]}
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seq = tvm.transform.Sequential(
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[
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tvm.tirx.transform.BindTarget(Target.current(allow_none=False)),
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tvm.relax.transform.FoldConstant(),
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tvm.relax.transform.DecomposeOpsForInference(),
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tvm.relax.transform.FoldConstant(),
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tvm.tirx.transform.BindTarget(tvm.target.Target.current(allow_none=False)),
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tvm.relax.transform.ConvertLayout(desired_layouts),
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tvm.relax.transform.Normalize(),
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tvm.relax.transform.FoldConstant(),
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tvm.relax.transform.LegalizeOps(),
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tvm.relax.transform.LegalizeOps(
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{"relax.nn.conv2d": legalize_adreno.conv2d_NCHWc_OIHWo}
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),
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tvm.relax.transform.FoldConstant(),
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tvm.relax.transform.AnnotateTIROpPattern(),
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tvm.relax.transform.FuseOps(),
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tvm.relax.transform.FuseTIR(),
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tvm.relax.transform.DeadCodeElimination(),
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tvm.relax.transform.Normalize(),
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]
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)
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mod = seq(mod)
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return mod
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def postprocess_pipeline(mod: IRModule) -> IRModule:
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seq = tvm.transform.Sequential(
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[
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tvm.relax.transform.ToNonDataflow(),
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tvm.relax.transform.RemovePurityChecking(),
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tvm.relax.transform.CallTIRRewrite(),
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tvm.relax.transform.Normalize(),
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tvm.relax.transform.StaticPlanBlockMemory(),
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tvm.relax.transform.LowerAllocTensor(),
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tvm.relax.transform.KillAfterLastUse(),
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tvm.relax.transform.LowerRuntimeBuiltin(),
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tvm.relax.transform.VMShapeLower(),
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tvm.relax.transform.AttachGlobalSymbol(),
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]
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)
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mod = seq(mod)
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return mod
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@pytest.mark.skipif(not env.build_flag_enabled("USE_RPC"), reason="need rpc")
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@pytest.mark.gpu
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@pytest.mark.skipif(not env.has_adreno_opencl(), reason="need adreno opencl")
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@pytest.mark.parametrize("backend", ["opencl"])
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@pytest.mark.parametrize("dtype", ["int8", "float16", "int16", "float32", "int32"])
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@pytest.mark.parametrize("channel_size", [64, 128])
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@pytest.mark.parametrize("read_width", [1, 2, 4, 8, 16])
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def test_texture_copy(backend, dtype, channel_size, read_width):
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remote = get_rpc()
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M, N, K = (256, 1024, 128)
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lanes = channel_size // DataType(dtype).bits
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if read_width > lanes:
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return
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@I.ir_module(s_tir=True)
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class TextureCopy:
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@T.prim_func(s_tir=True)
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def main(A: T.Buffer((M, N), dtype), B: T.Buffer((M, N), dtype)):
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T.func_attr({"global_symbol": "main"})
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for li, lj in T.grid(M, N):
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with T.sblock("Copy"):
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i, j = T.axis.remap("SS", [li, lj])
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B[i, j] = A[i, j]
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def schedule_texture_read(sch: s_tir.Schedule):
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B_blk = sch.get_sblock("Copy")
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Ai_block = sch.cache_read(B_blk, 0, "global.texture")
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sch.transform_layout(Ai_block, ("write", 0), lambda i, j: (i, j // lanes, j % lanes))
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def schedule_default(blk, lanes):
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i, j = sch.get_loops(blk)
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jo, jv = sch.split(j, [None, lanes])
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b = sch.fuse(i, jo)
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bx, tx = sch.split(b, [None, 256])
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sch.bind(bx, "blockIdx.x")
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sch.bind(tx, "threadIdx.x")
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sch.vectorize(jv)
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schedule_default(Ai_block, lanes)
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schedule_default(B_blk, read_width)
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mod = TextureCopy
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if remote is None:
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target = Target({"kind": backend, "device": "adreno"})
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else:
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target = Target(
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{"kind": backend, "device": "adreno"},
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{"kind": "llvm", "mtriple": "aarch64-linux-android"},
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)
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with target:
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mod = preprocess_pipeline(mod)
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sch = tvm.s_tir.Schedule(mod)
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schedule_texture_read(sch)
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mod = postprocess_pipeline(sch.mod)
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ex = relax.build(mod, target)
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load_path = "vm_library.so"
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inputs = [np.random.randint(0, 128, (M, N)).astype(dtype), np.zeros((M, N), dtype)]
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def run_and_check(rexec, remote_session):
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if remote_session is not None:
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dev = remote_session.cl()
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elif "opencl" in backend:
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dev = tvm.opencl(0)
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elif "vulkan" in backend:
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dev = tvm.vulkan(0)
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else:
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raise RuntimeError("Unsupported backend")
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if "vdevice" in mod.global_infos:
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device_arr = [dev for _ in range(len(mod.global_infos["vdevice"]))]
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else:
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device_arr = [dev]
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vm = relax.VirtualMachine(rexec, device_arr)
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inps = [tvm.runtime.tensor(inp, dev) for inp in inputs]
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vm["main"](*inps)
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np.testing.assert_equal(inps[-1].numpy(), inps[0].numpy())
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with tempfile.TemporaryDirectory() as temp_dir:
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if remote is not None:
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path = temp_dir + "/" + load_path
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ex.export_library(path, fcompile=ndk.create_shared, options=["-shared", "-fPIC", "-lm"])
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remote.upload(path)
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rexec = remote.load_module(load_path)
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try:
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run_and_check(rexec, remote)
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finally:
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remote.get_function("CloseRPCConnection")()
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else:
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tvm.testing.run_with_gpu_lock(run_and_check, ex, None)
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if __name__ == "__main__":
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tvm.testing.main()
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