Bump paddlepaddle from 2.4.2 to 2.5.1 in /src/bindings/python

[dependabot]

Bumps paddlepaddle from 2.4.2 to 2.5.1.

Release notes

Sourced from paddlepaddle's releases.

PaddlePaddle 2.5.0 Release Note

1. 重要更新

• 动静统一新架构：实现基础算子组合的动转静加编译器执行新模式，在ResNet50&Bert模型上完成动转静、组合算子、神经网络编译器优化加速全流程。动转静完成整图fallback核心功能开发，支持动转静失败时回退到动态图训练执行；组合算子设计一套包含150多个基础算子的基础算子体系，实现python层前向算子拆分机制和支持动、静态图的反向算子拆分机制，实现70多个常用前、反向算子的拆分；CINN编译器修复正确性问题，开发关键Pass，添加手工Schedule规则，实现内核代码自动生成，ResNet50模型性能提升12%，Bert模型性能提升10%。
• PHI算子库算子架构统一：将原算子体系下剩余的350+算子内核全部统一到PHI算子库中，以及原算子体系中的算子定义方式也都统一为PHI算子库的算子定义形式（基于YAML配置定义算子），提升了架构统一性，降低了框架开发的理解成本；将PHI算子库依赖的Fluid头文件全部解耦，并独立编译为动态链接库，为框架的二次开发提供更轻量的算子库复用方式；继续对飞桨框架中不规范的算子以及算子内核进行规范化调整，便于开发者理解，降低了硬件的接入成本。
• 静态图新执行器全面上线：静态图新执行器实现多项功能和性能优化，完成对原有多套旧执行器的统一和替换，成为静态图单卡和分布式训练python端入口以及动转静、控制流、CINN等后端默认使用的执行引擎，大幅提升框架调度性能，功能架构更加清晰，二次开发能力显著增强。
• Python API 支持0维tensor：为形状为[1,] 及形状为 [] 的张量定义了清晰的语义。
• 新的环境适配：适配了CUDA 12，并支持使用gcc12进行编译。

2. 不兼容升级

• 飞桨API支持0维tensor。飞桨之前用shape为[1]的1维tensor来替代0维tensor，这种替代方式和当前主流习惯有差异，增加模型的开发调试成本，有时还会导致非预期错误。本版本对需支持0维tensor的376个API进行了修正，和社区广泛使用的工具如EinOps等实现。例如，在之前的情况下，模型训练中输出的loss为1维tensor，如果要取出或打印loss，往往需要使用 loss.numpy()[0] 这样的代码。经过本次修改后，模型训练中输出的loss为0维tensor，使用 loss.numpy() 即可取出或打印loss，代码简短、易懂且符合业界使用习惯。
• paddle.fluid API全面退场。按照上个版本已预告的计划，本次退场了1116个paddle.fluidAPI及相关内部接口，剩余少量相关内部接口会在下个版本全部清理完成。fluid API属于飞桨2.0本计划移除但考虑到兼容性等因素延缓清理的历史API，本次退场清理不会影响基于飞桨2.0开发的程序，飞桨API体系也会更加简洁易懂。
• 旧版动态图Python端代码完成清理。至此，Python端仅使用新版动态图调用C++核心逻辑。
• 为统一静态图模型数据并行的训练方式，废弃原有的单进程多卡训练方式，包括 paddle.static.ParallelExecutor 和 paddle.static.CompiledProgram().with_data_parallel() 两个接口，原因是这套接口只支持单机多卡，不支持多机多卡，且底层执行性能较差。推荐统一使用多进程多卡训练方式，即 paddle.distributed.launch 接口来进行数据并行的分布式训练。该升级只影响静态图，不影响动态图和动转静训练，如果使用了废弃接口，请参考 数据并行 的文档修改模型代码。#50351，#50501，#51240，#51701，#51616，#51369，#52671
• 移除框架中原有的昇腾NPU和寒武纪MLU的适配代码，全部升级为CustomDevice插件式适配方式，并将昇腾NPU和寒武纪MLU的适配代码迁移至PaddleCustomDevice仓库。

3. 训练框架（含分布式）

Python API

API 支持0维tensor

• API输入支持0维tensor，涉及 paddle.reshape、paddle.trace、paddle.linalg.norm 等286个API。#53208, #53592, #47074, #53186, #47677, #49357, #50237, #46555, #47219, #47501, #47858, #47961, #48058, #48007, #49755, #51024, #51566, #51899, #49813, #47812, #47849, #47251, #53125, #53828, #51265, #47689, #48452, #49072, #48638, #49175, #49279, #50857, #49805, #47734, #45992, #49616, #49959, #50536, #49544, #49842, #46909, #49361, #50169, #48314, #48735, #49122, #49122, #49177, #49501, #49562, #49340, #49550, #49596, #49730, #49667, #49692, #49854, #49845, #49803, #49889, #49904, #49518, #49884, #49880, #49862, #49921, #49260, #49929, #49570, #49882, #50213, #49780, #50271, #50289, #50293, #49735, #50433, #49847, #50635, #50950, #50947, #49460, #53087, #51687, #52185, #54649
• API输出支持0维tensor，涉及 paddle.sum、paddle.min/max、paddle.any/all 等90个API。#52891, #52861, #52775, #52850, #52843, #52857, #51721, #53051, #53192, #52739, #52741, #53175, #51889, #53199, #53242, #53421
• 支持0维tensor后，修正原有不规范的代码，及对模型代码中的非规范用法进行提示和兼容。#51562, #51586, #51757, #52197, #54117。

new API

• 新增 jacobian 和 hessian API，用于科学计算。#53331
• 新增稀疏计算API。例如 paddle.sparse.reshape、paddle.sparse.sum 和 paddle.sparse.slice 等。#46694, #51513, #53794, #51406
• 新增其它API。例如 paddle.optimizer.LBFGS、paddle.index_put 和 paddle.logaddexp 等。#53314, #51912, #52886, #50843, #47282, #52284

动态图

新功能

• 新增了paddle.nn.utils.clip_grad_norm_用于支持梯度裁剪和paddle.Tensor.data_ptr用于获取Tensor数据的内存/显存的地址 PR49935, PR48235, PR49173
• 新增了saved_tensors_hooks机制，用于临时存放和取回用于反向计算使用的前向Tensor。 PR45763, PR46215, PR48124
• Tensor支持了pickler，用于支持Tensor的序列化。 PR47025, PR48179
• 新增了调试日志，反向出现nan/inf时打印前向Python堆栈 PR53217 PR52639 PR52729
• 新增了对expand_v2, tile, concat, assign, slice高阶微分的支持。PR45941, PR45942, PR45940, PR45879, PR45960

功能优化

• 优化了动态图的日志打印，包括日志内容优化、VLog级别优化、报错内容优化等。PR45783, PR46349, PR46934, PR47724
• 新增了FLAGS_auto_growth_chunk_size_in_mb用于auto_growth_allocator最小chunk size的设置 PR52204

bug fix

• 修复了一些算子的bug，包括：batch_norm, slice, set_value, scale, multinomial, adam, conv, transpose2_grad, conv2d_transpose_double_grad。PR47802, PR47634, PR47349, PR46124, PR46147, PR50388, PR48626, PR48519, PR50386, PR48432, PR51851
• 修复了PyLayer的一些错误问题。PR51740, PR47154, PR47323, PR54041, PR48533
• 确保sync_batch_norm在反向有序，防止错序导致hang或精度错误。PR52268, PR52860, PR52779
• 修复了linspace在AMP下的bug。PR46088
• 修复了Python C API错误调用导致Windows崩溃的问题。PR46833
• 修复了DataLoader可能遗漏删除/dev/shm的问题。PR48511
• 修复了paddle.grad的一些问题。PR47151
• 为不支持高阶微分的算子添加报错信息。PR47231
• 为python运算符添加numpyarray的支持。PR48229

... (truncated)

Commits

• 41ba14f Fix test_sparse_norm_op failure. (#55405) (#55637)
• fc1eac3 update recompute tunint unittest support other devices (#55165) (#55567)
• 4f9404a Fixed setuptools==57.4.0 (#55604)
• 170e64f update c++14 to 17 on cinn (#53861) (#55539)
• 3132054 fix the bug of test_fused_multi_transformer_op on cuda12 (#55431)
• 7ed818f [cherry-pick]fix data load error in static mode (#55545)
• 6a2db61 fix cudnn 8.7+ bug on cudnnConvolutionBiasActivationForward (#55412)
• 4910f40 fix bf16 optest and fix some testcases (#55414)
• 2817610 [cherry-pick] rename WITH_INFERENCE_NVTX to WITH_NVTX and fix compile error (...
• 32bbf74 fix bug when place 'use_cudnn' in extra (#54766) (#55167)
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