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// ----------------------------------------------------------------------------
// - Open3D: www.open3d.org -
// ----------------------------------------------------------------------------
// Copyright (c) 2018-2024 www.open3d.org
// SPDX-License-Identifier: MIT
// ----------------------------------------------------------------------------
#include "open3d/t/io/NumpyIO.h"
#include <cmath>
#include <limits>
#include "open3d/t/io/NumpyIO.h"
#include "open3d/utility/FileSystem.h"
#include "open3d/utility/Logging.h"
#include "tests/Tests.h"
#include "tests/core/CoreTest.h"
namespace open3d {
namespace tests {
class NumpyIOPermuteDevices : public PermuteDevices {};
INSTANTIATE_TEST_SUITE_P(Tensor,
NumpyIOPermuteDevices,
testing::ValuesIn(PermuteDevices::TestCases()));
TEST_P(NumpyIOPermuteDevices, NpyWriteRead) {
const core::Device device = GetParam();
const std::string file_name = "tensor.npy";
core::Tensor t;
core::Tensor t_load;
// 2x2 tensor.
t = core::Tensor::Init<float>({{1, 2}, {3, 4}}, device);
t.Save(file_name);
t_load = core::Tensor::Load(file_name);
EXPECT_TRUE(t.AllClose(t_load.To(device)));
// Non-contiguous tensor will be stored as contiguous tensor.
t = core::Tensor::Init<float>(
{{{0, 1, 2, 3}, {4, 5, 6, 7}, {8, 9, 10, 11}},
{{12, 13, 14, 15}, {16, 17, 18, 19}, {20, 21, 22, 23}}},
device);
// t[0:2:1, 0:3:2, 0:4:2]
t = t.Slice(0, 0, 2, 1).Slice(1, 0, 3, 2).Slice(2, 0, 4, 2);
t.Save(file_name);
EXPECT_FALSE(t.IsContiguous());
t_load = core::Tensor::Load(file_name);
EXPECT_TRUE(t_load.IsContiguous());
EXPECT_EQ(t_load.GetShape(), core::SizeVector({2, 2, 2}));
EXPECT_EQ(t_load.ToFlatVector<float>(),
std::vector<float>({0, 2, 8, 10, 12, 14, 20, 22}));
// {} tensor (scalar).
t = core::Tensor::Init<float>(3.14, device);
t.Save(file_name);
t_load = core::Tensor::Load(file_name);
EXPECT_TRUE(t.AllClose(t_load.To(device)));
// {0} tensor.
t = core::Tensor::Ones({0}, core::Float32, device);
t.Save(file_name);
t_load = core::Tensor::Load(file_name);
EXPECT_TRUE(t.AllClose(t_load.To(device)));
// {0, 0} tensor.
t = core::Tensor::Ones({0, 0}, core::Float32, device);
t.Save(file_name);
t_load = core::Tensor::Load(file_name);
EXPECT_TRUE(t.AllClose(t_load.To(device)));
// {0, 1, 0} tensor.
t = core::Tensor::Ones({0, 1, 0}, core::Float32, device);
t.Save(file_name);
t_load = core::Tensor::Load(file_name);
EXPECT_TRUE(t.AllClose(t_load.To(device)));
// Clean up.
utility::filesystem::RemoveFile(file_name);
}
TEST_P(NumpyIOPermuteDevices, NpzWriteRead) {
const core::Device device = GetParam();
const std::string file_name = "tensors.npz";
// Empty map.
t::io::WriteNpz(file_name, {});
std::unordered_map<std::string, core::Tensor> empty_tensor_map =
t::io::ReadNpz(file_name);
EXPECT_EQ(empty_tensor_map.size(), 0);
core::Tensor t;
core::Tensor t_load;
// t0: 2x2 tensor.
core::Tensor t0 = core::Tensor::Init<int32_t>({{1, 2}, {3, 4}}, device);
// t1: Non-contiguous tensor will be stored as contiguous tensor.
// t1 sliced with [0:2:1, 0:3:2, 0:4:2].
core::Tensor t1 = core::Tensor::Init<float>(
{{{0, 1, 2, 3}, {4, 5, 6, 7}, {8, 9, 10, 11}},
{{12, 13, 14, 15}, {16, 17, 18, 19}, {20, 21, 22, 23}}},
device);
t1 = t1.Slice(0, 0, 2, 1).Slice(1, 0, 3, 2).Slice(2, 0, 4, 2);
// t2: {} tensor (scalar).
core::Tensor t2 = core::Tensor::Init<float>(3.14, device);
// t3: {0} tensor.
core::Tensor t3 = core::Tensor::Ones({0}, core::Float32, device);
// t4: {0, 0} tensor.
core::Tensor t4 = core::Tensor::Ones({0, 0}, core::Float32, device);
// t5: {0, 1, 0} tensor.
core::Tensor t5 = core::Tensor::Ones({0, 1, 0}, core::Float32, device);
// Write t0 to t5.
t::io::WriteNpz(file_name, {{"t0", t0},
{"t1", t1},
{"t2", t2},
{"t3", t3},
{"t4", t4},
{"t5", t5}});
// Read from npz
std::unordered_map<std::string, core::Tensor> tensor_map =
t::io::ReadNpz(file_name);
EXPECT_EQ(tensor_map.size(), 6);
core::Tensor t0_load = tensor_map.at("t0");
EXPECT_TRUE(t0.AllClose(t0_load.To(device)));
EXPECT_EQ(t0.GetDtype(), t0_load.GetDtype());
core::Tensor t1_load = tensor_map.at("t1");
EXPECT_TRUE(t1.AllClose(t1_load.To(device)));
EXPECT_EQ(t1.GetDtype(), t1_load.GetDtype());
core::Tensor t2_load = tensor_map.at("t2");
EXPECT_TRUE(t2.AllClose(t2_load.To(device)));
EXPECT_EQ(t2.GetDtype(), t2_load.GetDtype());
core::Tensor t3_load = tensor_map.at("t3");
EXPECT_TRUE(t3.AllClose(t3_load.To(device)));
EXPECT_EQ(t3.GetDtype(), t3_load.GetDtype());
core::Tensor t4_load = tensor_map.at("t4");
EXPECT_TRUE(t4.AllClose(t4_load.To(device)));
EXPECT_EQ(t4.GetDtype(), t4_load.GetDtype());
core::Tensor t5_load = tensor_map.at("t5");
EXPECT_TRUE(t5.AllClose(t5_load.To(device)));
EXPECT_EQ(t5.GetDtype(), t5_load.GetDtype());
// Clean up.
utility::filesystem::RemoveFile(file_name);
}
} // namespace tests
} // namespace open3d
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