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[SPIRV] Support Bool buffer argument #7591

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Mar 5, 2021
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24 changes: 18 additions & 6 deletions src/target/spirv/codegen_spirv.cc
Original file line number Diff line number Diff line change
Expand Up @@ -45,10 +45,15 @@ std::vector<uint32_t> CodeGenSPIRV::BuildFunction(const PrimFunc& f, const std::
if (auto* ptr = arg->type_annotation.as<PointerTypeNode>()) {
auto* prim = ptr->element_type.as<PrimTypeNode>();
ICHECK(prim);
DataType value_type = prim->dtype;
DataType value_storage_type = prim->dtype;
if (value_storage_type == DataType::UInt(1)) {
// We need a physically addressable buffer type to support boolean tensors.
// The loaded byte is cast to bool inside the LoadNode visitor below.
value_storage_type = DataType::UInt(8);
}
spirv::Value arg_value =
builder_->BufferArgument(builder_->GetSType(value_type), 0, num_buffer);
storage_info_[arg.get()].UpdateContentType(value_type);
builder_->BufferArgument(builder_->GetSType(value_storage_type), 0, num_buffer);
storage_info_[arg.get()].UpdateContentType(value_storage_type);
var_map_[arg.get()] = arg_value;
} else {
LOG(FATAL) << "require all handles to be typed";
Expand Down Expand Up @@ -369,11 +374,18 @@ spirv::Value CodeGenSPIRV::VisitExpr_(const LoadNode* op) {
mask |= spv::MemoryAccessVolatileMask;
}
if (op->dtype.lanes() == 1) {
ICHECK_EQ(info.content_type, op->dtype)
<< "Vulkan only allow one type access to the same buffer";
spirv::Value index = MakeValue(op->index);
spirv::Value ptr = builder_->StructArrayAccess(ptr_type, buffer, index);
return builder_->MakeValue(spv::OpLoad, content_type, ptr, mask);
spirv::Value loaded = builder_->MakeValue(spv::OpLoad, content_type, ptr, mask);
if (op->dtype == DataType::UInt(1)) {
// A bool tensor is backed by a byte buffer, we cast to bool here.
auto bool_ty = builder_->GetSType(DataType::UInt(1));
return builder_->Cast(bool_ty, loaded);
} else {
ICHECK_EQ(info.content_type, op->dtype)
<< "Vulkan only allow one type access to the same buffer";
return loaded;
}
} else {
if (op->dtype.element_of() == info.content_type) {
// because content type is element type, we can only do scalarize load.
Expand Down
75 changes: 75 additions & 0 deletions tests/python/unittest/test_target_codegen_spirv.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,75 @@
# 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
import tvm.testing
from tvm import te
from tvm.topi.math import cast
import numpy as np


def test_bool_load():
def do_copy(A, B, n):
ib = tvm.tir.ir_builder.create()
A = ib.buffer_ptr(A)
B = ib.buffer_ptr(B)

tx = te.thread_axis("threadIdx.x")
bx = te.thread_axis("blockIdx.x")

max_threads = 32
ib.scope_attr(bx, "thread_extent", tvm.tir.indexdiv(n + max_threads - 1, max_threads))
ib.scope_attr(tx, "thread_extent", max_threads)
tid = bx * max_threads + tx

with ib.if_scope(tid < n):
B[tid] = cast(A[tid], "int32")

return ib.get()

n = 1024
A = te.placeholder((n,), name="A", dtype="bool")
B = te.placeholder((n,), name="B", dtype="int32")

target = "vulkan"

if not tvm.testing.device_enabled(target):
return

B = te.extern(
A.shape,
[A],
lambda ins, outs: do_copy(ins[0], outs[0], n),
name="bool_copy_ir",
dtype="int32",
)
s = te.create_schedule(B.op)

with tvm.transform.PassContext(opt_level=3):
func = tvm.build(s, [A, B], target)

ctx = tvm.context(target, 0)
a_np = np.random.uniform(size=n) > 0.5
b_np = np.zeros((n,), dtype="int32")
a = tvm.nd.array(a_np, ctx)
b = tvm.nd.array(b_np, ctx)
func(a, b)
ref = a_np.astype(np.int32)
tvm.testing.assert_allclose(b.asnumpy(), ref)


if __name__ == "__main__":
test_bool_load()