blob: 7d2360f22603d92a9f9077047a8e20c874e3a80e [file] [log] [blame]
/*
* 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.
*/
#include <gtest/gtest.h>
#include <tvm/runtime/logging.h>
#include <tvm/te/operation.h>
TEST(Tensor, Basic) {
using namespace tvm;
using namespace tvm::te;
Var m("m"), n("n"), l("l");
Tensor A = placeholder({m, l}, DataType::Float(32), "A");
Tensor B = placeholder({n, l}, DataType::Float(32), "B");
auto C = compute(
{m, n}, [&](Var i, Var j) { return A[i][j]; }, "C");
Tensor::Slice x = A[n];
}
TEST(Tensor, Reduce) {
using namespace tvm;
using namespace tvm::te;
Var m("m"), n("n"), l("l");
te::Tensor A = te::placeholder({m, l}, DataType::Float(32), "A");
te::Tensor B = te::placeholder({n, l}, DataType::Float(32), "B");
IterVar rv = reduce_axis(Range{0, l}, "k");
auto C = te::compute(
{m, n}, [&](Var i, Var j) { return sum(max(1 + A[i][rv] + 1, B[j][rv]), {rv}); }, "C");
}
TEST(Tensor, Indexing) {
using namespace tvm;
using namespace tvm::te;
Var x("x"), y("y");
te::Tensor A = te::placeholder({x, y}, DataType::Float(32), "A");
}