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mindspore/mindspore/lite
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lixian e847569108 optimizatino for winograd matmul 2020-08-25 22:19:39 +08:00
..
include fix bug 2020-08-23 21:21:10 +08:00
java add getFloatData function 2020-08-24 17:07:06 +08:00
minddata compile the core directory into a separate static library 2020-08-08 21:31:41 +08:00
nnacl optimizatino for winograd matmul 2020-08-25 22:19:39 +08:00
schema op_pooling+relu 2020-08-25 19:09:51 +08:00
src !5015 add mul add fusion pass 2020-08-25 22:02:14 +08:00
test matmul support fp16 2020-08-25 19:32:36 +08:00
tools !5015 add mul add fusion pass 2020-08-25 22:02:14 +08:00
CMakeLists.txt Add Convertor function for windows enviroment 2020-08-25 16:26:33 +08:00
README.md update README 2020-08-24 11:41:00 +08:00

README.md

ＭｉｎｄＳｐｏｒｅ的设计目标 １　端云一体化：ＩＲ统一，云侧训练模型可以在端侧重训；云侧混合精度训练与端侧混合精度推理协同提升推理性能； ２　高性能与轻量化：高性能内核计算库ｎｎａｃｌ，支持ｓｌｉｄｅ　ｗｉｎｄｏｗ、ｉｍ２ｃｏｌ＋ｇｅｍｍ、ｗｉｎｏｇｒａｄｅ等多种卷积算法，深度汇编指令优化；在线运行模块不依赖第三方库，保持框架的轻量化； ３　快捷部署：支持ＴｅｎｓｏｒＦｌｏｗ　Ｌｉｔｅ、Ｃａｆｆｅ、ＯＮＮＸ等多种格式的模型转换；提供量化、图片数据处理等功能，便利用户部署； ４　全场景覆盖：　Ｌｉｔｅ　＆　Ｍｉｃｒｏ覆盖手机、ＩｏＴ等各种智能设备