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paddlepaddle--paddle/test/cpp/compat/c10_SizesAndStrides_test.cc
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2026-07-13 12:40:42 +08:00

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// Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed 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 <ATen/Functions.h>
#include <ATen/core/TensorBody.h>
#include <ATen/cuda/EmptyTensor.h>
#include <ATen/native/cuda/Resize.h>
#include <ATen/ops/tensor.h>
#include <c10/core/ScalarType.h>
#include <c10/core/SymInt.h>
#include <c10/core/TensorOptions.h>
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#include <c10/cuda/CUDAFunctions.h>
#include <c10/cuda/CUDAGuard.h>
#endif
#include "ATen/ATen.h"
#include "gtest/gtest.h"
#include "paddle/phi/common/float16.h"
#include "torch/all.h"
TEST(TensorBaseTest, DimensionAPIs) {
// Test dimension related APIs
at::TensorBase tensor = at::ones({2, 3, 4}, at::kFloat);
// Test sizes()
auto sizes = tensor.sizes();
ASSERT_EQ(sizes.size(), 3);
ASSERT_EQ(sizes[0], 2);
ASSERT_EQ(sizes[1], 3);
ASSERT_EQ(sizes[2], 4);
// Test size(dim)
ASSERT_EQ(tensor.size(0), 2);
ASSERT_EQ(tensor.size(1), 3);
ASSERT_EQ(tensor.size(2), 4);
// Test strides()
auto strides = tensor.strides();
ASSERT_EQ(strides.size(), 3);
ASSERT_EQ(strides[0], 12); // 3*4
ASSERT_EQ(strides[1], 4); // 4
ASSERT_EQ(strides[2], 1); // contiguous
// Test stride(dim)
ASSERT_EQ(tensor.stride(0), 12);
ASSERT_EQ(tensor.stride(1), 4);
ASSERT_EQ(tensor.stride(2), 1);
// Test numel()
ASSERT_EQ(tensor.numel(), 24); // 2*3*4
// Test dim()/ndimension()
ASSERT_EQ(tensor.dim(), 3);
ASSERT_EQ(tensor.ndimension(), 3);
}
TEST(TestSymbolicInt, SymSizeAPI) {
// Test sym_size() API
at::TensorBase tensor = at::ones({2, 3, 4}, at::kFloat);
// Test sym_size(dim) returns c10::SymInt
c10::SymInt sym_size_0 = tensor.sym_size(0);
c10::SymInt sym_size_1 = tensor.sym_size(1);
c10::SymInt sym_size_2 = tensor.sym_size(2);
ASSERT_EQ(sym_size_0, 2);
ASSERT_EQ(sym_size_1, 3);
ASSERT_EQ(sym_size_2, 4);
// Test sym_size with negative index
c10::SymInt sym_size_neg1 = tensor.sym_size(-1);
c10::SymInt sym_size_neg2 = tensor.sym_size(-2);
c10::SymInt sym_size_neg3 = tensor.sym_size(-3);
ASSERT_EQ(sym_size_neg1, 4);
ASSERT_EQ(sym_size_neg2, 3);
ASSERT_EQ(sym_size_neg3, 2);
}
TEST(TestSymbolicInt, SymSizesAPI) {
// Test sym_sizes() API
at::TensorBase tensor = at::ones({2, 3, 4, 5}, at::kFloat);
// Test sym_sizes() returns c10::SymIntArrayRef
c10::SymIntArrayRef sym_sizes = tensor.sym_sizes();
ASSERT_EQ(sym_sizes.size(), 4);
ASSERT_EQ(sym_sizes[0], 2);
ASSERT_EQ(sym_sizes[1], 3);
ASSERT_EQ(sym_sizes[2], 4);
ASSERT_EQ(sym_sizes[3], 5);
}
TEST(TestSymbolicInt, SymStrideAPI) {
// Test sym_stride() API
at::TensorBase tensor = at::ones({2, 3, 4}, at::kFloat);
// Test sym_stride(dim) returns c10::SymInt
c10::SymInt sym_stride_0 = tensor.sym_stride(0);
c10::SymInt sym_stride_1 = tensor.sym_stride(1);
c10::SymInt sym_stride_2 = tensor.sym_stride(2);
ASSERT_EQ(sym_stride_0, 12); // 3*4
ASSERT_EQ(sym_stride_1, 4); // 4
ASSERT_EQ(sym_stride_2, 1); // contiguous
// Test sym_stride with negative index
c10::SymInt sym_stride_neg1 = tensor.sym_stride(-1);
c10::SymInt sym_stride_neg2 = tensor.sym_stride(-2);
ASSERT_EQ(sym_stride_neg1, 1);
ASSERT_EQ(sym_stride_neg2, 4);
}
TEST(TestSymbolicInt, SymStridesAPI) {
// Test sym_strides() API
at::TensorBase tensor = at::ones({2, 3, 4}, at::kFloat);
// Test sym_strides() returns c10::SymIntArrayRef
c10::SymIntArrayRef sym_strides = tensor.sym_strides();
ASSERT_EQ(sym_strides.size(), 3);
ASSERT_EQ(sym_strides[0], 12); // 3*4
ASSERT_EQ(sym_strides[1], 4); // 4
ASSERT_EQ(sym_strides[2], 1); // contiguous
}
TEST(TestSymbolicInt, SymNumelAPI) {
// Test sym_numel() API
at::TensorBase tensor = at::ones({2, 3, 4}, at::kFloat);
// Test sym_numel() returns c10::SymInt
c10::SymInt sym_numel = tensor.sym_numel();
ASSERT_EQ(sym_numel, 24); // 2*3*4
// Test with different shape
at::TensorBase tensor2 = at::ones({5, 6, 7, 8}, at::kFloat);
c10::SymInt sym_numel2 = tensor2.sym_numel();
ASSERT_EQ(sym_numel2, 1680); // 5*6*7*8
}
TEST(TestSymbolicInt, SymAPIsConsistency) {
// Test that sym_* APIs return values consistent with non-sym APIs
at::TensorBase tensor = at::ones({3, 4, 5, 6}, at::kFloat);
// Test sym_size vs size
for (int64_t i = 0; i < tensor.dim(); ++i) {
ASSERT_EQ(tensor.sym_size(i), tensor.size(i));
}
// Test sym_stride vs stride
for (int64_t i = 0; i < tensor.dim(); ++i) {
ASSERT_EQ(tensor.sym_stride(i), tensor.stride(i));
}
// Test sym_numel vs numel
ASSERT_EQ(tensor.sym_numel(), tensor.numel());
// Test sym_sizes vs sizes
auto sizes = tensor.sizes();
auto sym_sizes = tensor.sym_sizes();
ASSERT_EQ(sizes.size(), sym_sizes.size());
for (size_t i = 0; i < sizes.size(); ++i) {
ASSERT_EQ(sym_sizes[i], sizes[i]);
}
// Test sym_strides vs strides
auto strides = tensor.strides();
auto sym_strides = tensor.sym_strides();
ASSERT_EQ(strides.size(), sym_strides.size());
for (size_t i = 0; i < strides.size(); ++i) {
ASSERT_EQ(sym_strides[i], strides[i]);
}
}