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模型分析

卷积通道剪裁

蒸馏

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SANAS API文档

class SANAS

SANAS（Simulated Annealing Neural Architecture Search）是基于模拟退火算法进行模型结构搜索的算法，一般用于离散搜索任务。

@@ -322,83 +349,53 @@ for step in range(100): ### 回传score sa_nas.reward(float(finally_reward[1])) -
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class Pruner

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示例：


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量化训练API

量化配置

quant_config_default = {
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 quant_program = quant.quant_embedding(infer_program, place, config)
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paddleslim.nas 提供的搜索空间：

  1. 根据原本模型结构构造搜索空间：
@@ -253,83 +282,53 @@ class ResNetBlockSpace2(SearchSpaceBase): conv = fluid.layers.conv2d(input, num_filters, filter_size, stride, name=name+'_conv') bn = fluid.layers.batch_norm(conv, act=act, name=name+'_bn') return bn -
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merge(teacher_program, student_program, data_name_map, place, scope=fluid.global_scope(), name_prefix='teacher_')

该方法将两个fluid program（teacher_program, student_program）融合为一个program，并将融合得到的program返回。在融合的program中，可以为其中合适的teacher特征图和student特征图添加蒸馏损失函数，从而达到用teacher模型的暗知识（Dark Knowledge）指导student模型学习的目的。

参数：

@@ -330,83 +361,53 @@ with fluid.program_guard(main_program):
  1. 建议与student_program使用同一个命名空间，以避免一些未指定名称的variables(例如tmp_0, tmp_1...)多次定义为同一名称出现命名冲突
  2. 建议在添加蒸馏loss时指定一个命名空间前缀，具体用法请参考Paddle官方文档fluid.name_scope
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PaddleSlim

PaddleSlim是PaddlePaddle框架的一个子模块，主要用于压缩图像领域模型。在PaddleSlim中，不仅实现了目前主流的网络剪枝、量化、蒸馏三种压缩策略，还实现了超参数搜索和小模型网络结构搜索功能。在后续版本中，会添加更多的压缩策略，以及完善对NLP领域模型的支持。

功能

    @@ -215,83 +240,53 @@ python setup.py install
  • Paddle分割库：介绍如何在分割库中使用PaddleSlim。
  • PaddleLite：介绍如何使用预测库PaddleLite部署PaddleSlim产出的模型。
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硬件延时评估表

硬件延时评估表用于快速评估一个模型在特定硬件环境和推理引擎上的推理速度。 该文档主要用于定义PaddleSlim支持的硬件延时评估表的格式。

概述

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  • h_in (int) - 输入 Tensor 的特征高度。
  • w_in (int) - 输入 Tensor 的特征宽度。
  • latency (float) - 当前op的延时时间
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    蒸馏

    蒸馏demo默认使用ResNet50作为teacher网络，MobileNet作为student网络，此外还支持将teacher和student换成models目录支持的任意模型。

    demo中对teahcer模型和student模型的一层特征图添加了l2_loss的蒸馏损失函数，使用时也可根据需要选择fsp_loss, soft_label_loss以及自定义的loss函数。

    训练默认使用的是cifar10数据集，piecewise_decay学习率衰减策略，momentum优化器进行120轮蒸馏训练。使用者也可以简单地用args参数切换为使用ImageNet数据集，cosine_decay学习率衰减策略等其他训练配置。

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    离线量化demo文档

    Embedding量化demo文档

    NAS

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    网络结构搜索示例

    本示例介绍如何使用网络结构搜索接口，搜索到一个更小或者精度更高的模型，该文档仅介绍paddleslim中SANAS的使用及如何利用SANAS得到模型结构，完整示例代码请参考sa_nas_mobilenetv2.py或者block_sa_nas_mobilenetv2.py。

    接口介绍

    请参考。

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    6. 回传score

    sa_nas.reward(score)
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    在线量化示例

    本示例介绍如何使用在线量化接口，来对训练好的分类模型进行量化, 可以减少模型的存储空间和显存占用。

    接口介绍

    请参考 量化API文档。

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    Embedding量化示例

    本示例介绍如何使用Embedding量化的接口 paddleslim.quant.quant_embedding 。quant_embedding接口将网络中的Embedding参数从float32类型量化到 8-bit整数类型，在几乎不损失模型精度的情况下减少模型的存储空间和显存占用。

    接口介绍请参考 量化API文档。

    该接口对program的修改：

    @@ -337,83 +364,53 @@ step:1 2719 epoch:9 acc:0.153 -

    量化后的模型保存在./output_quant中，可看到量化后的参数'emb.int8'的大小为3.9M, 在./v1_cpu5_b100_lr1dir中可看到量化前的参数'emb'的大小为16M。

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    离线量化示例

    本示例介绍如何使用离线量化接口paddleslim.quant.quant_post来对训练好的分类模型进行离线量化, 该接口无需对模型进行训练就可得到量化模型，减少模型的存储空间和显存占用。

    接口介绍

    请参考 量化API文档。

    @@ -209,83 +236,49 @@ 
    top1_acc/top5_acc= [0.70141864 0.89086477]
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    从以上精度对比可以看出，对mobilenet在imagenet上的分类模型进行离线量化后 top1精度损失为0.77%， top5精度损失为0.46%.

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All rights reserved. - + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 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- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/fonts/glyphicons-halflings-regular.ttf b/fonts/glyphicons-halflings-regular.ttf deleted file mode 100644 index 1413fc609ab6f21774de0cb7e01360095584f65b..0000000000000000000000000000000000000000 Binary files a/fonts/glyphicons-halflings-regular.ttf and /dev/null differ diff --git a/fonts/glyphicons-halflings-regular.woff b/fonts/glyphicons-halflings-regular.woff deleted file mode 100644 index 9e612858f802245ddcbf59788a0db942224bab35..0000000000000000000000000000000000000000 Binary files a/fonts/glyphicons-halflings-regular.woff and /dev/null differ diff --git a/fonts/glyphicons-halflings-regular.woff2 b/fonts/glyphicons-halflings-regular.woff2 deleted file mode 100644 index 64539b54c3751a6d9adb44c8e3a45ba5a73b77f0..0000000000000000000000000000000000000000 Binary files a/fonts/glyphicons-halflings-regular.woff2 and /dev/null differ diff --git a/img/grid.png b/img/grid.png deleted file mode 100644 index 878c3ed5c196539c4e2da35b7787ab08e98b9cca..0000000000000000000000000000000000000000 Binary files a/img/grid.png and /dev/null differ diff --git a/index.html b/index.html index 1b321ebd5d3fff753da96d09f07949782a9326ef..7b2e4d629545427a3d8306db277dcfba3062d804 100644 --- a/index.html +++ b/index.html @@ -1,161 +1,180 @@ - - - - - - - - - - My Docs - - - - - - + + + + + + + + + + Welcome to MkDocs - PaddleSlim + - - - - - + + + + + + + + + + + + - + - +
    -
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    Welcome to MkDocs

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    • Docs »
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    • Welcome to MkDocs
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    Welcome to MkDocs

    For full documentation visit mkdocs.org.

    Commands

      @@ -169,88 +188,54 @@ docs/ index.md # The documentation homepage. ... # Other markdown pages, images and other files. -
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    Documentation built with MkDocs.

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    + + + - + diff --git a/js/base.js b/js/base.js deleted file mode 100644 index 4755f43439bc998bbd2cb4f6dca4d34c67a8f0a8..0000000000000000000000000000000000000000 --- a/js/base.js +++ /dev/null @@ -1,216 +0,0 @@ -function getSearchTerm() -{ - var sPageURL = window.location.search.substring(1); - var sURLVariables = sPageURL.split('&'); - for (var i = 0; i < sURLVariables.length; i++) - { - var sParameterName = sURLVariables[i].split('='); - if (sParameterName[0] == 'q') - { - return sParameterName[1]; - } - } -} - -$(document).ready(function() { - - var search_term = getSearchTerm(), - $search_modal = $('#mkdocs_search_modal'), - $keyboard_modal = $('#mkdocs_keyboard_modal'); - - if(search_term){ - $search_modal.modal(); - } - - // make sure search input gets autofocus everytime modal opens. - $search_modal.on('shown.bs.modal', function () { - $search_modal.find('#mkdocs-search-query').focus(); - }); - - // Close search modal when result is selected - // The links get added later so listen to parent - $('#mkdocs-search-results').click(function(e) { - if ($(e.target).is('a')) { - $search_modal.modal('hide'); - } - }); - - // Populate keyboard modal with proper Keys - $keyboard_modal.find('.help.shortcut kbd')[0].innerHTML = keyCodes[shortcuts.help]; - $keyboard_modal.find('.prev.shortcut kbd')[0].innerHTML = keyCodes[shortcuts.previous]; - $keyboard_modal.find('.next.shortcut kbd')[0].innerHTML = keyCodes[shortcuts.next]; - $keyboard_modal.find('.search.shortcut kbd')[0].innerHTML = keyCodes[shortcuts.search]; - - // Keyboard navigation - document.addEventListener("keydown", function(e) { - if ($(e.target).is(':input')) return true; - var key = e.which || e.keyCode || window.event && window.event.keyCode; - var page; - switch (key) { - case shortcuts.next: - page = $('[role="navigation"] a:contains(Next):first').prop('href'); - break; - case shortcuts.previous: - page = $('[role="navigation"] a:contains(Previous):first').prop('href'); - break; - case shortcuts.search: - e.preventDefault(); - $keyboard_modal.modal('hide'); - $search_modal.modal('show'); - $search_modal.find('#mkdocs-search-query').focus(); - break; - case shortcuts.help: - $search_modal.modal('hide'); - $keyboard_modal.modal('show'); - break; - default: break; - } - if (page) { - $keyboard_modal.modal('hide'); - window.location.href = page; - } - }); - - $('table').addClass('table table-striped table-hover'); - - // Improve the scrollspy behaviour when users click on a TOC item. - $(".bs-sidenav a").on("click", function() { - var clicked = this; - setTimeout(function() { - var active = $('.nav li.active a'); - active = active[active.length - 1]; - if (clicked !== active) { - $(active).parent().removeClass("active"); - $(clicked).parent().addClass("active"); - } - }, 50); - }); - -}); - - -$('body').scrollspy({ - target: '.bs-sidebar', - offset: 100 -}); - -/* Prevent disabled links from causing a page reload */ -$("li.disabled a").click(function() { - event.preventDefault(); -}); - -// See https://www.cambiaresearch.com/articles/15/javascript-char-codes-key-codes -// We only list common keys below. 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