issue/896 - 为c++和python中的tensor添加打印函数 #930
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pengcheng888
commented
Jan 15, 2026
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| import infinicore.context as context | ||
| import infinicore.nn as nn | ||
| from infinicore._tensor_str import printoptions, set_printoptions |
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torch中把print的一些 函数调用放到了_tensor_str.py文件中，于是也新建了一个 _tensor_str
pengcheng888
commented
Jan 15, 2026
| "strided_from_blob", | ||
| "zeros", | ||
| "set_printoptions", | ||
| "printoptions", |
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torch中存在一下两个函数
"set_printoptions"：全局配置的函数
"printoptions"： 临时配置的函数
pengcheng888
commented
Jan 15, 2026
| std::string repr = m1.extra_repr(); | ||
| spdlog::debug("Linear module representation: {}", repr); | ||
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| // Test forward with residual connection |
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c++的linear有个版移除了一个函数，导致c++测试编译不过。于是，在src/infinicore-test/test_nn_module.cc中注释或删除了传递的参数
pengcheng888
commented
Jan 15, 2026
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| // Prepare test data (stored outside loop to ensure lifetime) | ||
| bool bool_data[4] = {true, false, true, false}; | ||
| int8_t i8_data[4] = {-128, -64, 32, 127}; |
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由于infinicore.Tensor没有rand函数，没法生成随机数，所以就事前固定了测试数据
pengcheng888
commented
Jan 15, 2026
| set_installdir(os.getenv("INFINI_ROOT") or (os.getenv(is_host("windows") and "HOMEPATH" or "HOME") .. "/.infini")) | ||
| target_end() | ||
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| target("infinicore-test") |
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c++的infinicore的测试脚本出错，于是添加上了缺少的"infinicore_cpp_api"依赖
pengcheng888
commented
Jan 15, 2026
| template <typename T> | ||
| T item_impl(const std::byte *data, DataType dtype) { | ||
| switch (dtype) { | ||
| case DataType::F16: { |
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由于c++没有原生的F16和BF16格式数据，为了能cout打印，把F16和BF16转成了float类型去显示
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目标版本
main
功能描述
c++和python中的tensor添加打印函数，可以全局或临时配置一下参数：
(1) 触发省略的阈值：数据量过多时，显示部分数据；
(2) 每行显示字符数量：显示宽度合适，自动换行；
(3) 精度：设置显示的小数点位数；
(4) edgeitems: 省略显示时，设置显示的数据数量
c++的cout函数支持的类型： BOOL，I8，I16，I32，I64，U8，U16，U32，U64，BF16，F16，F32，F64
python的print函数支持的类型： BOOL，I8，I16，I32，I64，U8，BF16，F16，F32，F64
python代码std::cout测试：
临时修改后，自动恢复原始配置
全局修改后，配置生效
print不同的数据类型
python代码print测试：
临时修改后，自动恢复原始配置
全局修改后，配置生效
cout不同的数据类型
