Modified: incubator/singa/site/trunk/docs/model_zoo/examples/imagenet/resnet/README.html URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/docs/model_zoo/examples/imagenet/resnet/README.html?rev=1862313&r1=1862312&r2=1862313&view=diff ============================================================================== --- incubator/singa/site/trunk/docs/model_zoo/examples/imagenet/resnet/README.html (original) +++ incubator/singa/site/trunk/docs/model_zoo/examples/imagenet/resnet/README.html Sat Jun 29 14:42:24 2019 @@ -9,7 +9,7 @@ <meta name="viewport" content="width=device-width, initial-scale=1.0"> - <title>name: Resnets on ImageNet SINGA version: 1.1 SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz license: Apache V2, https://github.com/facebook/fb.resnet.torch/blob/master/LICENSE — incubator-singa 2.0.0 documentation</title> + <title>Image Classification using Residual Networks — incubator-singa 2.0.0 documentation</title> @@ -163,11 +163,7 @@ <li><a href="../../../../../index.html">Docs</a> »</li> - <li>name: Resnets on ImageNet -SINGA version: 1.1 -SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz -license: Apache V2, https://github.com/facebook/fb.resnet.torch/blob/master/LICENSE</li> + <li>Image Classification using Residual Networks</li> <li class="wy-breadcrumbs-aside"> @@ -201,33 +197,25 @@ license: Apache V2, https://github.com/f KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ---><hr class="docutils" /> -<div class="section" id="name-resnets-on-imagenet-singa-version-1-1-singa-commit-45ec92d8ffc1fa1385a9307fdf07e21da939ee2f-parameter-url-https-s3-ap-southeast-1-amazonaws-com-dlfile-resnet-resnet-18-tar-gz-license-apache-v2-https-github-com-facebook-fb-resnet-torch-blob-master-license"> -<h1>name: Resnets on ImageNet -SINGA version: 1.1 -SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz -license: Apache V2, https://github.com/facebook/fb.resnet.torch/blob/master/LICENSE<a class="headerlink" href="#name-resnets-on-imagenet-singa-version-1-1-singa-commit-45ec92d8ffc1fa1385a9307fdf07e21da939ee2f-parameter-url-https-s3-ap-southeast-1-amazonaws-com-dlfile-resnet-resnet-18-tar-gz-license-apache-v2-https-github-com-facebook-fb-resnet-torch-blob-master-license" title="Permalink to this headline">¶</a></h1> -</div> -<div class="section" id="image-classification-using-residual-networks"> +--><div class="section" id="image-classification-using-residual-networks"> <h1>Image Classification using Residual Networks<a class="headerlink" href="#image-classification-using-residual-networks" title="Permalink to this headline">¶</a></h1> -<p>In this example, we convert Residual Networks trained on <a class="reference external" href="https://github.com/facebook/fb.resnet.torch";>Torch</a> to SINGA for image classification.</p> +<p>In this example, we convert Residual Networks trained on <a class="reference external" href="https://github.com/facebook/fb.resnet.torch";>Torch</a> to SINGA for image classification. Tested on [SINGA commit] with the <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz";>parameters pretrained by Torch</a></p> <div class="section" id="instructions"> <h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2> <ul> -<li><p class="first">Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p> +<li><p>Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/synset_words.txt $ tar xvf resnet-18.tar.gz </pre></div> </div> </li> -<li><p class="first">Usage</p> +<li><p>Usage</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ python serve.py -h </pre></div> </div> </li> -<li><p class="first">Example</p> +<li><p>Example</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> # use cpu $ python serve.py --use_cpu --parameter_file resnet-18.pickle --model resnet --depth 18 & # use gpu @@ -236,13 +224,13 @@ license: Apache V2, https://github.com/f </div> <p>The parameter files for the following model and depth configuration pairs are provided:</p> <ul class="simple"> -<li>resnet (original resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz";>18</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-34.tar.gz";>34</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-101.tar.gz";>101</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-152.tar.gz";>152</a></li> -<li>addbn (resnet with a batch normalization layer after the addition), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-50.tar.gz";>50</a></li> -<li>wrn (wide resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/wrn-50-2.tar.gz";>50</a></li> -<li>preact (resnet with pre-activation) <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-200.tar.gz";>200</a></li> +<li><p>resnet (original resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz";>18</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-34.tar.gz";>34</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-101.tar.gz";>101</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-152.tar.gz";>152</a></p></li> +<li><p>addbn (resnet with a batch normalization layer after the addition), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-50.tar.gz";>50</a></p></li> +<li><p>wrn (wide resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/wrn-50-2.tar.gz";>50</a></p></li> +<li><p>preact (resnet with pre-activation) <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-200.tar.gz";>200</a></p></li> </ul> </li> -<li><p class="first">Submit images for classification</p> +<li><p>Submit images for classification</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api
Modified: incubator/singa/site/trunk/docs/model_zoo/examples/imagenet/vgg/README.html URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/docs/model_zoo/examples/imagenet/vgg/README.html?rev=1862313&r1=1862312&r2=1862313&view=diff ============================================================================== --- incubator/singa/site/trunk/docs/model_zoo/examples/imagenet/vgg/README.html (original) +++ incubator/singa/site/trunk/docs/model_zoo/examples/imagenet/vgg/README.html Sat Jun 29 14:42:24 2019 @@ -9,7 +9,7 @@ <meta name="viewport" content="width=device-width, initial-scale=1.0"> - <title>name: VGG models on ImageNet SINGA version: 1.1.1 SINGA commit: license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py — incubator-singa 2.0.0 documentation</title> + <title>Image Classification using VGG — incubator-singa 2.0.0 documentation</title> @@ -163,10 +163,7 @@ <li><a href="../../../../../index.html">Docs</a> »</li> - <li>name: VGG models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py</li> + <li>Image Classification using VGG</li> <li class="wy-breadcrumbs-aside"> @@ -200,33 +197,26 @@ license: https://github.com/pytorch/visi KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ---><hr class="docutils" /> -<div class="section" id="name-vgg-models-on-imagenet-singa-version-1-1-1-singa-commit-license-https-github-com-pytorch-vision-blob-master-torchvision-models-vgg-py"> -<h1>name: VGG models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py<a class="headerlink" href="#name-vgg-models-on-imagenet-singa-version-1-1-1-singa-commit-license-https-github-com-pytorch-vision-blob-master-torchvision-models-vgg-py" title="Permalink to this headline">¶</a></h1> -</div> -<div class="section" id="image-classification-using-vgg"> +--><div class="section" id="image-classification-using-vgg"> <h1>Image Classification using VGG<a class="headerlink" href="#image-classification-using-vgg" title="Permalink to this headline">¶</a></h1> <p>In this example, we convert VGG on <a class="reference external" href="https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py";>PyTorch</a> to SINGA for image classification.</p> <div class="section" id="instructions"> <h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2> <ul> -<li><p class="first">Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p> +<li><p>Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11.tar.gz $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/synset_words.txt $ tar xvf vgg11.tar.gz </pre></div> </div> </li> -<li><p class="first">Usage</p> +<li><p>Usage</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ python serve.py -h </pre></div> </div> </li> -<li><p class="first">Example</p> +<li><p>Example</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> # use cpu $ python serve.py --use_cpu --parameter_file vgg11.pickle --depth 11 & # use gpu @@ -235,11 +225,11 @@ to SINGA for image classification.</p> </div> <p>The parameter files for the following model and depth configuration pairs are provided:</p> <ul class="simple"> -<li>Without batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11.tar.gz";>11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13.tar.gz";>13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16.tar.gz";>16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19.tar.gz";>19</a></li> -<li>With batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11_bn.tar.gz";>11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13_bn.tar.gz";>13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16_bn.tar.gz";>16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19_bn.tar.gz";>19</a></li> +<li><p>Without batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11.tar.gz";>11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13.tar.gz";>13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16.tar.gz";>16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19.tar.gz";>19</a></p></li> +<li><p>With batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11_bn.tar.gz";>11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13_bn.tar.gz";>13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16_bn.tar.gz";>16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19_bn.tar.gz";>19</a></p></li> </ul> </li> -<li><p class="first">Submit images for classification</p> +<li><p>Submit images for classification</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api Modified: incubator/singa/site/trunk/docs/model_zoo/examples/index.html URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/docs/model_zoo/examples/index.html?rev=1862313&r1=1862312&r2=1862313&view=diff ============================================================================== --- incubator/singa/site/trunk/docs/model_zoo/examples/index.html (original) +++ incubator/singa/site/trunk/docs/model_zoo/examples/index.html Sat Jun 29 14:42:24 2019 @@ -212,52 +212,27 @@ </li> </ul> </li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/densenet/README.html">name: DenseNet models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py</a></li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/densenet/README.html#image-classification-using-densenet">Image Classification using DenseNet</a><ul> +<li class="toctree-l1"><a class="reference internal" href="imagenet/densenet/README.html">Image Classification using DenseNet</a><ul> <li class="toctree-l2"><a class="reference internal" href="imagenet/densenet/README.html#instructions">Instructions</a></li> <li class="toctree-l2"><a class="reference internal" href="imagenet/densenet/README.html#details">Details</a></li> </ul> </li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/googlenet/README.html">name: GoogleNet on ImageNet -SINGA version: 1.0.1 -SINGA commit: 8c990f7da2de220e8a012c6a8ecc897dc7532744 -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/bvlc_googlenet.tar.gz -parameter_sha1: 0a88e8948b1abca3badfd8d090d6be03f8d7655d -license: unrestricted https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet</a></li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/googlenet/README.html#image-classification-using-googlenet">Image Classification using GoogleNet</a><ul> +<li class="toctree-l1"><a class="reference internal" href="imagenet/googlenet/README.html">Image Classification using GoogleNet</a><ul> <li class="toctree-l2"><a class="reference internal" href="imagenet/googlenet/README.html#instructions">Instructions</a></li> <li class="toctree-l2"><a class="reference internal" href="imagenet/googlenet/README.html#details">Details</a></li> </ul> </li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/inception/README.html">name: Inception V4 on ImageNet -SINGA version: 1.1.1 -SINGA commit: -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz -parameter_sha1: 5fdd6f5d8af8fd10e7321d9b38bb87ef14e80d56 -license: https://github.com/tensorflow/models/tree/master/slim</a></li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/inception/README.html#image-classification-using-inception-v4">Image Classification using Inception V4</a><ul> +<li class="toctree-l1"><a class="reference internal" href="imagenet/inception/README.html">Image Classification using Inception V4</a><ul> <li class="toctree-l2"><a class="reference internal" href="imagenet/inception/README.html#instructions">Instructions</a></li> <li class="toctree-l2"><a class="reference internal" href="imagenet/inception/README.html#details">Details</a></li> </ul> </li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/resnet/README.html">name: Resnets on ImageNet -SINGA version: 1.1 -SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz -license: Apache V2, https://github.com/facebook/fb.resnet.torch/blob/master/LICENSE</a></li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/resnet/README.html#image-classification-using-residual-networks">Image Classification using Residual Networks</a><ul> +<li class="toctree-l1"><a class="reference internal" href="imagenet/resnet/README.html">Image Classification using Residual Networks</a><ul> <li class="toctree-l2"><a class="reference internal" href="imagenet/resnet/README.html#instructions">Instructions</a></li> <li class="toctree-l2"><a class="reference internal" href="imagenet/resnet/README.html#details">Details</a></li> </ul> </li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/vgg/README.html">name: VGG models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py</a></li> -<li class="toctree-l1"><a class="reference internal" href="imagenet/vgg/README.html#image-classification-using-vgg">Image Classification using VGG</a><ul> +<li class="toctree-l1"><a class="reference internal" href="imagenet/vgg/README.html">Image Classification using VGG</a><ul> <li class="toctree-l2"><a class="reference internal" href="imagenet/vgg/README.html#instructions">Instructions</a></li> <li class="toctree-l2"><a class="reference internal" href="imagenet/vgg/README.html#details">Details</a></li> </ul> Modified: incubator/singa/site/trunk/docs/model_zoo/examples/mnist/README.html URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/docs/model_zoo/examples/mnist/README.html?rev=1862313&r1=1862312&r2=1862313&view=diff ============================================================================== --- incubator/singa/site/trunk/docs/model_zoo/examples/mnist/README.html (original) +++ incubator/singa/site/trunk/docs/model_zoo/examples/mnist/README.html Sat Jun 29 14:42:24 2019 @@ -205,9 +205,8 @@ MNIST dataset. The RBM model and its hyp <div class="section" id="running-instructions"> <h2>Running instructions<a class="headerlink" href="#running-instructions" title="Permalink to this headline">¶</a></h2> <ol> -<li><p class="first">Download the pre-processed <a class="reference external" href="https://github.com/mnielsen/neural-networks-and-deep-learning/raw/master/data/mnist.pkl.gz";>MNIST dataset</a></p> -</li> -<li><p class="first">Start the training</p> +<li><p>Download the pre-processed <a class="reference external" href="https://github.com/mnielsen/neural-networks-and-deep-learning/raw/master/data/mnist.pkl.gz";>MNIST dataset</a></p></li> +<li><p>Start the training</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">python</span> <span class="n">train</span><span class="o">.</span><span class="n">py</span> <span class="n">mnist</span><span class="o">.</span><span class="n">pkl</span><span class="o">.</span><span class="n">gz</span> </pre></div> </div> Modified: incubator/singa/site/trunk/docs/model_zoo/imagenet/alexnet/README.html URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/docs/model_zoo/imagenet/alexnet/README.html?rev=1862313&r1=1862312&r2=1862313&view=diff ============================================================================== --- incubator/singa/site/trunk/docs/model_zoo/imagenet/alexnet/README.html (original) +++ incubator/singa/site/trunk/docs/model_zoo/imagenet/alexnet/README.html Sat Jun 29 14:42:24 2019 @@ -36,8 +36,8 @@ <link rel="stylesheet" href="../../../../_static/pygments.css" type="text/css" /> <link rel="index" title="Index" href="../../../../genindex.html" /> <link rel="search" title="Search" href="../../../../search.html" /> - <link rel="next" title="name: DenseNet models on ImageNet SINGA version: 1.1.1 SINGA commit: license: https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py"; href="../densenet/README.html" /> - <link rel="prev" title="Train a RBM model against MNIST dataset" href="../../mnist/README.html" /> + <link rel="next" title="name: GoogleNet on ImageNet SINGA version: 1.0.1 SINGA commit: 8c990f7da2de220e8a012c6a8ecc897dc7532744 parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/bvlc_googlenet.tar.gz parameter_sha1: 0a88e8948b1abca3badfd8d090d6be03f8d7655d license: unrestricted https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet"; href="../googlenet/README.html" /> + <link rel="prev" title="Train Char-RNN over plain text" href="../../char-rnn/README.html" /> <link href="../../../../_static/style.css" rel="stylesheet" type="text/css"> <!--link href="../../../../_static/fontawesome-all.min.css" rel="stylesheet" type="text/css"--> <link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.0.13/css/all.css"; integrity="sha384-DNOHZ68U8hZfKXOrtjWvjxusGo9WQnrNx2sqG0tfsghAvtVlRW3tvkXWZh58N9jp" crossorigin="anonymous"> @@ -104,6 +104,7 @@ <li class="toctree-l1 current"><a class="reference internal" href="../../../index.html">Documentation</a><ul class="current"> <li class="toctree-l2"><a class="reference internal" href="../../../installation.html">Installation</a></li> <li class="toctree-l2"><a class="reference internal" href="../../../software_stack.html">Software Stack</a></li> +<li class="toctree-l2"><a class="reference internal" href="../../../benchmark.html">Benchmark for Distributed training</a></li> <li class="toctree-l2"><a class="reference internal" href="../../../device.html">Device</a></li> <li class="toctree-l2"><a class="reference internal" href="../../../tensor.html">Tensor</a></li> <li class="toctree-l2"><a class="reference internal" href="../../../layer.html">Layer</a></li> @@ -121,16 +122,10 @@ <li class="toctree-l2 current"><a class="reference internal" href="../../index.html">Model Zoo</a><ul class="current"> <li class="toctree-l3"><a class="reference internal" href="../../cifar10/README.html">Train CNN over Cifar-10</a></li> <li class="toctree-l3"><a class="reference internal" href="../../char-rnn/README.html">Train Char-RNN over plain text</a></li> -<li class="toctree-l3"><a class="reference internal" href="../../mnist/README.html">Train a RBM model against MNIST dataset</a></li> <li class="toctree-l3 current"><a class="current reference internal" href="#">Train AlexNet over ImageNet</a><ul> <li class="toctree-l4"><a class="reference internal" href="#instructions">Instructions</a></li> </ul> </li> -<li class="toctree-l3"><a class="reference internal" href="../densenet/README.html">name: DenseNet models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py</a></li> -<li class="toctree-l3"><a class="reference internal" href="../densenet/README.html#image-classification-using-densenet">Image Classification using DenseNet</a></li> <li class="toctree-l3"><a class="reference internal" href="../googlenet/README.html">name: GoogleNet on ImageNet SINGA version: 1.0.1 SINGA commit: 8c990f7da2de220e8a012c6a8ecc897dc7532744 @@ -138,24 +133,6 @@ parameter_url: https://s3-ap-southeast-1 parameter_sha1: 0a88e8948b1abca3badfd8d090d6be03f8d7655d license: unrestricted https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet</a></li> <li class="toctree-l3"><a class="reference internal" href="../googlenet/README.html#image-classification-using-googlenet">Image Classification using GoogleNet</a></li> -<li class="toctree-l3"><a class="reference internal" href="../inception/README.html">name: Inception V4 on ImageNet -SINGA version: 1.1.1 -SINGA commit: -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz -parameter_sha1: 5fdd6f5d8af8fd10e7321d9b38bb87ef14e80d56 -license: https://github.com/tensorflow/models/tree/master/slim</a></li> -<li class="toctree-l3"><a class="reference internal" href="../inception/README.html#image-classification-using-inception-v4">Image Classification using Inception V4</a></li> -<li class="toctree-l3"><a class="reference internal" href="../resnet/README.html">name: Resnets on ImageNet -SINGA version: 1.1 -SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz -license: Apache V2, https://github.com/facebook/fb.resnet.torch/blob/master/LICENSE</a></li> -<li class="toctree-l3"><a class="reference internal" href="../resnet/README.html#image-classification-using-residual-networks">Image Classification using Residual Networks</a></li> -<li class="toctree-l3"><a class="reference internal" href="../vgg/README.html">name: VGG models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py</a></li> -<li class="toctree-l3"><a class="reference internal" href="../vgg/README.html#image-classification-using-vgg">Image Classification using VGG</a></li> </ul> </li> </ul> @@ -244,24 +221,7 @@ license: https://github.com/pytorch/visi <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article";> <div itemprop="articleBody"> - <!-- - Licensed to the Apache Software Foundation (ASF) under one - or more contributor license agreements. See the NOTICE file - distributed with this work for additional information - regarding copyright ownership. The ASF licenses this file - to you under the Apache License, Version 2.0 (the - "License"); you may not use this file except in compliance - with the License. You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, - software distributed under the License is distributed on an - "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - KIND, either express or implied. See the License for the - specific language governing permissions and limitations - under the License. ---><div class="section" id="train-alexnet-over-imagenet"> + <div class="section" id="train-alexnet-over-imagenet"> <h1>Train AlexNet over ImageNet<a class="headerlink" href="#train-alexnet-over-imagenet" title="Permalink to this headline">¶</a></h1> <p>Convolution neural network (CNN) is a type of feed-forward neural network widely used for image and video classification. In this example, we will @@ -278,17 +238,17 @@ options in CMakeLists.txt or run <code c <div class="section" id="data-download"> <h3>Data download<a class="headerlink" href="#data-download" title="Permalink to this headline">¶</a></h3> <ul class="simple"> -<li>Please refer to step1-3 on <a class="reference external" href="https://github.com/amd/OpenCL-caffe/wiki/Instructions-to-create-ImageNet-2012-data";>Instructions to create ImageNet 2012 data</a> -to download and decompress the data.</li> -<li>You can download the training and validation list by +<li><p>Please refer to step1-3 on <a class="reference external" href="https://github.com/amd/OpenCL-caffe/wiki/Instructions-to-create-ImageNet-2012-data";>Instructions to create ImageNet 2012 data</a> +to download and decompress the data.</p></li> +<li><p>You can download the training and validation list by <a class="reference external" href="https://github.com/BVLC/caffe/blob/master/data/ilsvrc12/get_ilsvrc_aux.sh";>get_ilsvrc_aux.sh</a> -or from <a class="reference external" href="http://www.image-net.org/download-images";>Imagenet</a>.</li> +or from <a class="reference external" href="http://www.image-net.org/download-images";>Imagenet</a>.</p></li> </ul> </div> <div class="section" id="data-preprocessing"> <h3>Data preprocessing<a class="headerlink" href="#data-preprocessing" title="Permalink to this headline">¶</a></h3> <ul> -<li><p class="first">Assuming you have downloaded the data and the list. +<li><p>Assuming you have downloaded the data and the list. Now we should transform the data into binary files. You can run:</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">sh</span> <span class="n">create_data</span><span class="o">.</span><span class="n">sh</span> </pre></div> @@ -296,15 +256,15 @@ Now we should transform the data into bi <p>The script will generate a test file(<code class="docutils literal notranslate"><span class="pre">test.bin</span></code>), a mean file(<code class="docutils literal notranslate"><span class="pre">mean.bin</span></code>) and several training files(<code class="docutils literal notranslate"><span class="pre">trainX.bin</span></code>) in the specified output folder.</p> </li> -<li><p class="first">You can also change the parameters in <code class="docutils literal notranslate"><span class="pre">create_data.sh</span></code>.</p> +<li><p>You can also change the parameters in <code class="docutils literal notranslate"><span class="pre">create_data.sh</span></code>.</p> <ul class="simple"> -<li><code class="docutils literal notranslate"><span class="pre">-trainlist</span> <span class="pre"><file></span></code>: the file of training list;</li> -<li><code class="docutils literal notranslate"><span class="pre">-trainfolder</span> <span class="pre"><folder></span></code>: the folder of training images;</li> -<li><code class="docutils literal notranslate"><span class="pre">-testlist</span> <span class="pre"><file></span></code>: the file of test list;</li> -<li><code class="docutils literal notranslate"><span class="pre">-testfolder</span> <span class="pre"><floder></span></code>: the folder of test images;</li> -<li><code class="docutils literal notranslate"><span class="pre">-outdata</span> <span class="pre"><folder></span></code>: the folder to save output files, including mean, training and test files. -The script will generate these files in the specified folder;</li> -<li><code class="docutils literal notranslate"><span class="pre">-filesize</span> <span class="pre"><int></span></code>: number of training images that stores in each binary file.</li> +<li><p><code class="docutils literal notranslate"><span class="pre">-trainlist</span> <span class="pre"><file></span></code>: the file of training list;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-trainfolder</span> <span class="pre"><folder></span></code>: the folder of training images;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-testlist</span> <span class="pre"><file></span></code>: the file of test list;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-testfolder</span> <span class="pre"><floder></span></code>: the folder of test images;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-outdata</span> <span class="pre"><folder></span></code>: the folder to save output files, including mean, training and test files. +The script will generate these files in the specified folder;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-filesize</span> <span class="pre"><int></span></code>: number of training images that stores in each binary file.</p></li> </ul> </li> </ul> @@ -312,25 +272,25 @@ The script will generate these files in <div class="section" id="training"> <h3>Training<a class="headerlink" href="#training" title="Permalink to this headline">¶</a></h3> <ul> -<li><p class="first">After preparing data, you can run the following command to train the Alexnet model.</p> +<li><p>After preparing data, you can run the following command to train the Alexnet model.</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="n">sh</span> <span class="n">run</span><span class="o">.</span><span class="n">sh</span> </pre></div> </div> </li> -<li><p class="first">You may change the parameters in <code class="docutils literal notranslate"><span class="pre">run.sh</span></code>.</p> +<li><p>You may change the parameters in <code class="docutils literal notranslate"><span class="pre">run.sh</span></code>.</p> <ul class="simple"> -<li><code class="docutils literal notranslate"><span class="pre">-epoch</span> <span class="pre"><int></span></code>: number of epoch to be trained, default is 90;</li> -<li><code class="docutils literal notranslate"><span class="pre">-lr</span> <span class="pre"><float></span></code>: base learning rate, the learning rate will decrease each 20 epochs, -more specifically, <code class="docutils literal notranslate"><span class="pre">lr</span> <span class="pre">=</span> <span class="pre">lr</span> <span class="pre">*</span> <span class="pre">exp(0.1</span> <span class="pre">*</span> <span class="pre">(epoch</span> <span class="pre">/</span> <span class="pre">20))</span></code>;</li> -<li><code class="docutils literal notranslate"><span class="pre">-batchsize</span> <span class="pre"><int></span></code>: batchsize, it should be changed regarding to your memory;</li> -<li><code class="docutils literal notranslate"><span class="pre">-filesize</span> <span class="pre"><int></span></code>: number of training images that stores in each binary file, it is the -same as the <code class="docutils literal notranslate"><span class="pre">filesize</span></code> in data preprocessing;</li> -<li><code class="docutils literal notranslate"><span class="pre">-ntrain</span> <span class="pre"><int></span></code>: number of training images;</li> -<li><code class="docutils literal notranslate"><span class="pre">-ntest</span> <span class="pre"><int></span></code>: number of test images;</li> -<li><code class="docutils literal notranslate"><span class="pre">-data</span> <span class="pre"><folder></span></code>: the folder which stores the binary files, it is exactly the output -folder in data preprocessing step;</li> -<li><code class="docutils literal notranslate"><span class="pre">-pfreq</span> <span class="pre"><int></span></code>: the frequency(in batch) of printing current model status(loss and accuracy);</li> -<li><code class="docutils literal notranslate"><span class="pre">-nthreads</span> <span class="pre"><int></span></code>: the number of threads to load data which feed to the model.</li> +<li><p><code class="docutils literal notranslate"><span class="pre">-epoch</span> <span class="pre"><int></span></code>: number of epoch to be trained, default is 90;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-lr</span> <span class="pre"><float></span></code>: base learning rate, the learning rate will decrease each 20 epochs, +more specifically, <code class="docutils literal notranslate"><span class="pre">lr</span> <span class="pre">=</span> <span class="pre">lr</span> <span class="pre">*</span> <span class="pre">exp(0.1</span> <span class="pre">*</span> <span class="pre">(epoch</span> <span class="pre">/</span> <span class="pre">20))</span></code>;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-batchsize</span> <span class="pre"><int></span></code>: batchsize, it should be changed regarding to your memory;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-filesize</span> <span class="pre"><int></span></code>: number of training images that stores in each binary file, it is the +same as the <code class="docutils literal notranslate"><span class="pre">filesize</span></code> in data preprocessing;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-ntrain</span> <span class="pre"><int></span></code>: number of training images;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-ntest</span> <span class="pre"><int></span></code>: number of test images;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-data</span> <span class="pre"><folder></span></code>: the folder which stores the binary files, it is exactly the output +folder in data preprocessing step;</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-pfreq</span> <span class="pre"><int></span></code>: the frequency(in batch) of printing current model status(loss and accuracy);</p></li> +<li><p><code class="docutils literal notranslate"><span class="pre">-nthreads</span> <span class="pre"><int></span></code>: the number of threads to load data which feed to the model.</p></li> </ul> </li> </ul> @@ -346,10 +306,10 @@ folder in data preprocessing step;</li> <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> - <a href="../densenet/README.html" class="btn btn-neutral float-right" title="name: DenseNet models on ImageNet SINGA version: 1.1.1 SINGA commit: license: https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py"; accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a> + <a href="../googlenet/README.html" class="btn btn-neutral float-right" title="name: 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http://svn.apache.org/viewvc/incubator/singa/site/trunk/docs/model_zoo/imagenet/googlenet/README.html?rev=1862313&r1=1862312&r2=1862313&view=diff ============================================================================== --- incubator/singa/site/trunk/docs/model_zoo/imagenet/googlenet/README.html (original) +++ incubator/singa/site/trunk/docs/model_zoo/imagenet/googlenet/README.html Sat Jun 29 14:42:24 2019 @@ -36,8 +36,8 @@ <link rel="stylesheet" href="../../../../_static/pygments.css" type="text/css" /> <link rel="index" title="Index" href="../../../../genindex.html" /> <link rel="search" title="Search" href="../../../../search.html" /> - <link rel="next" title="name: Inception V4 on ImageNet SINGA version: 1.1.1 SINGA commit: parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz parameter_sha1: 5fdd6f5d8af8fd10e7321d9b38bb87ef14e80d56 license: https://github.com/tensorflow/models/tree/master/slim"; href="../inception/README.html" /> - <link rel="prev" title="name: DenseNet models on ImageNet SINGA version: 1.1.1 SINGA commit: license: https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py"; href="../densenet/README.html" /> + <link rel="next" title="Download SINGA" href="../../../../downloads.html" /> + <link rel="prev" title="Train AlexNet over ImageNet" href="../alexnet/README.html" /> <link href="../../../../_static/style.css" rel="stylesheet" type="text/css"> <!--link href="../../../../_static/fontawesome-all.min.css" rel="stylesheet" type="text/css"--> <link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.0.13/css/all.css"; integrity="sha384-DNOHZ68U8hZfKXOrtjWvjxusGo9WQnrNx2sqG0tfsghAvtVlRW3tvkXWZh58N9jp" crossorigin="anonymous"> @@ -104,6 +104,7 @@ <li class="toctree-l1 current"><a class="reference internal" href="../../../index.html">Documentation</a><ul class="current"> <li class="toctree-l2"><a class="reference internal" href="../../../installation.html">Installation</a></li> <li class="toctree-l2"><a class="reference internal" href="../../../software_stack.html">Software Stack</a></li> +<li class="toctree-l2"><a class="reference internal" href="../../../benchmark.html">Benchmark for Distributed training</a></li> <li class="toctree-l2"><a class="reference internal" href="../../../device.html">Device</a></li> <li class="toctree-l2"><a class="reference internal" href="../../../tensor.html">Tensor</a></li> <li class="toctree-l2"><a class="reference internal" href="../../../layer.html">Layer</a></li> @@ -121,13 +122,7 @@ <li class="toctree-l2 current"><a class="reference internal" href="../../index.html">Model Zoo</a><ul class="current"> <li class="toctree-l3"><a class="reference internal" href="../../cifar10/README.html">Train CNN over Cifar-10</a></li> <li class="toctree-l3"><a class="reference internal" href="../../char-rnn/README.html">Train Char-RNN over plain text</a></li> -<li class="toctree-l3"><a class="reference internal" href="../../mnist/README.html">Train a RBM model against MNIST dataset</a></li> <li class="toctree-l3"><a class="reference internal" href="../alexnet/README.html">Train AlexNet over ImageNet</a></li> -<li class="toctree-l3"><a class="reference internal" href="../densenet/README.html">name: DenseNet models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py</a></li> -<li class="toctree-l3"><a class="reference internal" href="../densenet/README.html#image-classification-using-densenet">Image Classification using DenseNet</a></li> <li class="toctree-l3 current"><a class="current reference internal" href="#">name: GoogleNet on ImageNet SINGA version: 1.0.1 SINGA commit: 8c990f7da2de220e8a012c6a8ecc897dc7532744 @@ -139,24 +134,6 @@ license: unrestricted https://github.com <li class="toctree-l4"><a class="reference internal" href="#details">Details</a></li> </ul> </li> -<li class="toctree-l3"><a class="reference internal" href="../inception/README.html">name: Inception V4 on ImageNet -SINGA version: 1.1.1 -SINGA commit: -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz -parameter_sha1: 5fdd6f5d8af8fd10e7321d9b38bb87ef14e80d56 -license: https://github.com/tensorflow/models/tree/master/slim</a></li> -<li class="toctree-l3"><a class="reference internal" href="../inception/README.html#image-classification-using-inception-v4">Image Classification using Inception V4</a></li> -<li class="toctree-l3"><a class="reference internal" href="../resnet/README.html">name: Resnets on ImageNet -SINGA version: 1.1 -SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz -license: Apache V2, https://github.com/facebook/fb.resnet.torch/blob/master/LICENSE</a></li> -<li class="toctree-l3"><a class="reference internal" href="../resnet/README.html#image-classification-using-residual-networks">Image Classification using Residual Networks</a></li> -<li class="toctree-l3"><a class="reference internal" href="../vgg/README.html">name: VGG models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py</a></li> -<li class="toctree-l3"><a class="reference internal" href="../vgg/README.html#image-classification-using-vgg">Image Classification using VGG</a></li> </ul> </li> </ul> @@ -250,24 +227,7 @@ license: unrestricted https://github.com <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article";> <div itemprop="articleBody"> - <!-- - Licensed to the Apache Software Foundation (ASF) under one - or more contributor license agreements. See the NOTICE file - distributed with this work for additional information - regarding copyright ownership. The ASF licenses this file - to you under the Apache License, Version 2.0 (the - "License"); you may not use this file except in compliance - with the License. You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, - software distributed under the License is distributed on an - "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - KIND, either express or implied. See the License for the - specific language governing permissions and limitations - under the License. ---><hr class="docutils" /> + <hr class="docutils" /> <div class="section" id="name-googlenet-on-imagenet-singa-version-1-0-1-singa-commit-8c990f7da2de220e8a012c6a8ecc897dc7532744-parameter-url-https-s3-ap-southeast-1-amazonaws-com-dlfile-bvlc-googlenet-tar-gz-parameter-sha1-0a88e8948b1abca3badfd8d090d6be03f8d7655d-license-unrestricted-https-github-com-bvlc-caffe-tree-master-models-bvlc-googlenet"> <h1>name: GoogleNet on ImageNet SINGA version: 1.0.1 @@ -282,13 +242,13 @@ license: unrestricted https://github.com <div class="section" id="instructions"> <h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2> <ul> -<li><p class="first">Download the parameter checkpoint file into this folder</p> +<li><p>Download the parameter checkpoint file into this folder</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/bvlc_googlenet.tar.gz $ tar xvf bvlc_googlenet.tar.gz </pre></div> </div> </li> -<li><p class="first">Run the program</p> +<li><p>Run the program</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> # use cpu $ python serve.py -C & # use gpu @@ -296,7 +256,7 @@ license: unrestricted https://github.com </pre></div> </div> </li> -<li><p class="first">Submit images for classification</p> +<li><p>Submit images for classification</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api @@ -347,10 +307,10 @@ Refer to <a class="reference external" h <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> - <a href="../inception/README.html" 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internal" href="../vgg/README.html#image-classification-using-vgg">Image Classification using VGG</a></li> -</ul> -</li> -</ul> -</li> + <ul> +<li class="toctree-l1"><a class="reference internal" href="../../../index.html">Documentation</a></li> <li class="toctree-l1"><a class="reference internal" href="../../../../downloads.html">Download SINGA</a></li> <li class="toctree-l1"><a class="reference internal" href="../../../../security.html">Security</a></li> </ul> @@ -224,10 +163,6 @@ license: https://github.com/pytorch/visi <li><a href="../../../../index.html">Docs</a> »</li> - <li><a href="../../../index.html">Documentation</a> »</li> - - <li><a href="../../index.html">Model Zoo</a> »</li> - <li>name: Inception V4 on ImageNet SINGA version: 1.1.1 SINGA commit: @@ -250,24 +185,7 @@ license: https://github.com/tensorflow/m <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article";> <div itemprop="articleBody"> - <!-- - Licensed to the Apache Software Foundation (ASF) under one - or more contributor license agreements. See the NOTICE file - distributed with this work for additional information - regarding copyright ownership. The ASF licenses this file - to you under the Apache License, Version 2.0 (the - "License"); you may not use this file except in compliance - with the License. You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, - software distributed under the License is distributed on an - "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - KIND, either express or implied. See the License for the - specific language governing permissions and limitations - under the License. ---><hr class="docutils" /> + <hr class="docutils" /> <div class="section" id="name-inception-v4-on-imagenet-singa-version-1-1-1-singa-commit-parameter-url-https-s3-ap-southeast-1-amazonaws-com-dlfile-inception-v4-tar-gz-parameter-sha1-5fdd6f5d8af8fd10e7321d9b38bb87ef14e80d56-license-https-github-com-tensorflow-models-tree-master-slim"> <h1>name: Inception V4 on ImageNet SINGA version: 1.1.1 @@ -282,15 +200,14 @@ license: https://github.com/tensorflow/m <div class="section" id="instructions"> <h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2> <ul> -<li><p class="first">Download the parameter checkpoint file</p> +<li><p>Download the parameter checkpoint file</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ wget $ tar xvf inception_v4.tar.gz </pre></div> </div> </li> -<li><p class="first">Download <a class="reference external" href="https://github.com/BVLC/caffe/blob/master/data/ilsvrc12/get_ilsvrc_aux.sh";>synset_word.txt</a> file.</p> -</li> -<li><p class="first">Run the program</p> +<li><p>Download <a class="reference external" href="https://github.com/BVLC/caffe/blob/master/data/ilsvrc12/get_ilsvrc_aux.sh";>synset_word.txt</a> file.</p></li> +<li><p>Run the program</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> # use cpu $ python serve.py -C & # use gpu @@ -298,7 +215,7 @@ license: https://github.com/tensorflow/m </pre></div> </div> </li> -<li><p class="first">Submit images for classification</p> +<li><p>Submit images for classification</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api @@ -324,15 +241,6 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<ul> +<li class="toctree-l1"><a class="reference internal" href="../../../index.html">Documentation</a></li> <li class="toctree-l1"><a class="reference internal" href="../../../../downloads.html">Download SINGA</a></li> <li class="toctree-l1"><a class="reference internal" href="../../../../security.html">Security</a></li> </ul> @@ -224,10 +163,6 @@ license: https://github.com/pytorch/visi <li><a href="../../../../index.html">Docs</a> »</li> - <li><a href="../../../index.html">Documentation</a> »</li> - - <li><a href="../../index.html">Model Zoo</a> »</li> - <li>name: Resnets on ImageNet SINGA version: 1.1 SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f @@ -249,24 +184,7 @@ license: Apache V2, https://github.com/f <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article";> <div itemprop="articleBody"> - <!-- - Licensed to the Apache Software Foundation (ASF) under one - or more contributor license agreements. See the NOTICE file - distributed with this work for additional information - regarding copyright ownership. The ASF licenses this file - to you under the Apache License, Version 2.0 (the - "License"); you may not use this file except in compliance - with the License. You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, - software distributed under the License is distributed on an - "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - KIND, either express or implied. See the License for the - specific language governing permissions and limitations - under the License. ---><hr class="docutils" /> + <hr class="docutils" /> <div class="section" id="name-resnets-on-imagenet-singa-version-1-1-singa-commit-45ec92d8ffc1fa1385a9307fdf07e21da939ee2f-parameter-url-https-s3-ap-southeast-1-amazonaws-com-dlfile-resnet-resnet-18-tar-gz-license-apache-v2-https-github-com-facebook-fb-resnet-torch-blob-master-license"> <h1>name: Resnets on ImageNet SINGA version: 1.1 @@ -280,19 +198,19 @@ license: Apache V2, https://github.com/f <div class="section" id="instructions"> <h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2> <ul> -<li><p class="first">Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p> +<li><p>Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/synset_words.txt $ tar xvf resnet-18.tar.gz </pre></div> </div> </li> -<li><p class="first">Usage</p> +<li><p>Usage</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ python serve.py -h </pre></div> </div> </li> -<li><p class="first">Example</p> +<li><p>Example</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> # use cpu $ python serve.py --use_cpu --parameter_file resnet-18.pickle --model resnet --depth 18 & # use gpu @@ -301,13 +219,13 @@ license: Apache V2, https://github.com/f </div> <p>The parameter files for the following model and depth configuration pairs are provided:</p> <ul class="simple"> -<li>resnet (original resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz";>18</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-34.tar.gz";>34</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-101.tar.gz";>101</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-152.tar.gz";>152</a></li> -<li>addbn (resnet with a batch normalization layer after the addition), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-50.tar.gz";>50</a></li> -<li>wrn (wide resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/wrn-50-2.tar.gz";>50</a></li> -<li>preact (resnet with pre-activation) <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-200.tar.gz";>200</a></li> +<li><p>resnet (original resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz";>18</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-34.tar.gz";>34</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-101.tar.gz";>101</a>|<a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-152.tar.gz";>152</a></p></li> +<li><p>addbn (resnet with a batch normalization layer after the addition), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-50.tar.gz";>50</a></p></li> +<li><p>wrn (wide resnet), <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/wrn-50-2.tar.gz";>50</a></p></li> +<li><p>preact (resnet with pre-activation) <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-200.tar.gz";>200</a></p></li> </ul> </li> -<li><p class="first">Submit images for classification</p> +<li><p>Submit images for classification</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api @@ -334,15 +252,6 @@ the convert.py program.</p> </div> <footer> - <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> - - <a href="../vgg/README.html" class="btn btn-neutral float-right" title="name: VGG models on ImageNet SINGA version: 1.1.1 SINGA commit: license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py"; accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a> - - - <a href="../inception/README.html" class="btn btn-neutral float-left" title="name: Inception V4 on ImageNet SINGA version: 1.1.1 SINGA commit: parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz parameter_sha1: 5fdd6f5d8af8fd10e7321d9b38bb87ef14e80d56 license: https://github.com/tensorflow/models/tree/master/slim"; accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left"></span> Previous</a> - - </div> - <hr/> Modified: incubator/singa/site/trunk/docs/model_zoo/imagenet/vgg/README.html URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/docs/model_zoo/imagenet/vgg/README.html?rev=1862313&r1=1862312&r2=1862313&view=diff ============================================================================== --- incubator/singa/site/trunk/docs/model_zoo/imagenet/vgg/README.html (original) +++ incubator/singa/site/trunk/docs/model_zoo/imagenet/vgg/README.html Sat Jun 29 14:42:24 2019 @@ -36,8 +36,6 @@ <link rel="stylesheet" href="../../../../_static/pygments.css" type="text/css" /> <link rel="index" title="Index" href="../../../../genindex.html" /> <link rel="search" title="Search" 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class="toctree-l2"><a class="reference internal" href="../../../installation.html">Installation</a></li> -<li class="toctree-l2"><a class="reference internal" href="../../../software_stack.html">Software Stack</a></li> -<li class="toctree-l2"><a class="reference internal" href="../../../device.html">Device</a></li> -<li class="toctree-l2"><a class="reference internal" href="../../../tensor.html">Tensor</a></li> -<li class="toctree-l2"><a class="reference internal" href="../../../layer.html">Layer</a></li> -<li class="toctree-l2"><a class="reference internal" href="../../../net.html">FeedForward Net</a></li> -<li class="toctree-l2"><a class="reference internal" href="../../../initializer.html">Initializer</a></li> -<li class="toctree-l2"><a class="reference internal" href="../../../loss.html">Loss</a></li> -<li class="toctree-l2"><a class="reference internal" href="../../../metric.html">Metric</a></li> -<li class="toctree-l2"><a class="reference internal" 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href="../../char-rnn/README.html">Train Char-RNN over plain text</a></li> -<li class="toctree-l3"><a class="reference internal" href="../../mnist/README.html">Train a RBM model against MNIST dataset</a></li> -<li class="toctree-l3"><a class="reference internal" href="../alexnet/README.html">Train AlexNet over ImageNet</a></li> -<li class="toctree-l3"><a class="reference internal" href="../densenet/README.html">name: DenseNet models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py</a></li> -<li class="toctree-l3"><a class="reference internal" href="../densenet/README.html#image-classification-using-densenet">Image Classification using DenseNet</a></li> -<li class="toctree-l3"><a class="reference internal" href="../googlenet/README.html">name: GoogleNet on ImageNet -SINGA version: 1.0.1 -SINGA commit: 8c990f7da2de220e8a012c6a8ecc897dc7532744 -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/bvlc_googlenet.tar.gz -parameter_sha1: 0a88e8948b1abca3badfd8d090d6be03f8d7655d -license: unrestricted https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet</a></li> -<li class="toctree-l3"><a class="reference internal" href="../googlenet/README.html#image-classification-using-googlenet">Image Classification using GoogleNet</a></li> -<li class="toctree-l3"><a class="reference internal" href="../inception/README.html">name: Inception V4 on ImageNet -SINGA version: 1.1.1 -SINGA commit: -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz -parameter_sha1: 5fdd6f5d8af8fd10e7321d9b38bb87ef14e80d56 -license: https://github.com/tensorflow/models/tree/master/slim</a></li> -<li class="toctree-l3"><a class="reference internal" href="../inception/README.html#image-classification-using-inception-v4">Image Classification using Inception V4</a></li> -<li class="toctree-l3"><a class="reference internal" href="../resnet/README.html">name: Resnets on ImageNet -SINGA version: 1.1 -SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f -parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz -license: Apache V2, https://github.com/facebook/fb.resnet.torch/blob/master/LICENSE</a></li> -<li class="toctree-l3"><a class="reference internal" href="../resnet/README.html#image-classification-using-residual-networks">Image Classification using Residual Networks</a></li> -<li class="toctree-l3 current"><a class="current reference internal" href="#">name: VGG models on ImageNet -SINGA version: 1.1.1 -SINGA commit: -license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py</a></li> -<li class="toctree-l3"><a class="reference internal" href="#image-classification-using-vgg">Image Classification using VGG</a><ul> -<li class="toctree-l4"><a class="reference internal" href="#instructions">Instructions</a></li> -<li class="toctree-l4"><a class="reference internal" href="#details">Details</a></li> -</ul> -</li> -</ul> -</li> -</ul> -</li> + <ul> +<li class="toctree-l1"><a class="reference internal" href="../../../index.html">Documentation</a></li> <li class="toctree-l1"><a class="reference internal" href="../../../../downloads.html">Download SINGA</a></li> <li class="toctree-l1"><a class="reference internal" href="../../../../security.html">Security</a></li> </ul> @@ -224,10 +163,6 @@ license: https://github.com/pytorch/visi <li><a href="../../../../index.html">Docs</a> »</li> - <li><a href="../../../index.html">Documentation</a> »</li> - - <li><a href="../../index.html">Model Zoo</a> »</li> - <li>name: VGG models on ImageNet SINGA version: 1.1.1 SINGA commit: @@ -248,24 +183,7 @@ license: https://github.com/pytorch/visi <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article";> <div itemprop="articleBody"> - <!-- - Licensed to the Apache Software Foundation (ASF) under one - or more contributor license agreements. See the NOTICE file - distributed with this work for additional information - regarding copyright ownership. The ASF licenses this file - to you under the Apache License, Version 2.0 (the - "License"); you may not use this file except in compliance - with the License. You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, - software distributed under the License is distributed on an - "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - KIND, either express or implied. See the License for the - specific language governing permissions and limitations - under the License. ---><hr class="docutils" /> + <hr class="docutils" /> <div class="section" id="name-vgg-models-on-imagenet-singa-version-1-1-1-singa-commit-license-https-github-com-pytorch-vision-blob-master-torchvision-models-vgg-py"> <h1>name: VGG models on ImageNet SINGA version: 1.1.1 @@ -279,32 +197,32 @@ to SINGA for image classification.</p> <div class="section" id="instructions"> <h2>Instructions<a class="headerlink" href="#instructions" title="Permalink to this headline">¶</a></h2> <ul> -<li><p class="first">Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p> +<li><p>Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11.tar.gz $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/synset_words.txt $ tar xvf vgg11.tar.gz </pre></div> </div> </li> -<li><p class="first">Usage</p> +<li><p>Usage</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ python serve.py -h </pre></div> </div> </li> -<li><p class="first">Example</p> +<li><p>Example</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> # use cpu - $ python serve.py --use_cpu --parameter_file vgg11.pickle --depth 11 & + $ python serve.py --use_cpu --parameter_file vgg11.pickle --depth 11 --use_cpu & # use gpu - $ python serve.py --parameter_file vgg11.pickle --depth 11 & + $ python serve.py --use_cpu --parameter_file vgg11.pickle --depth 11 & </pre></div> </div> <p>The parameter files for the following model and depth configuration pairs are provided:</p> <ul class="simple"> -<li>Without batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11.tar.gz";>11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13.tar.gz";>13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16.tar.gz";>16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19.tar.gz";>19</a></li> -<li>With batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11_bn.tar.gz";>11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13_bn.tar.gz";>13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16_bn.tar.gz";>16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19_bn.tar.gz";>19</a></li> +<li><p>Without batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11.tar.gz";>11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13.tar.gz";>13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16.tar.gz";>16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19.tar.gz";>19</a></p></li> +<li><p>With batch-normalization, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11_bn.tar.gz";>11</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg13_bn.tar.gz";>13</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg16_bn.tar.gz";>16</a>, <a class="reference external" href="https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg19_bn.tar.gz";>19</a></p></li> </ul> </li> -<li><p class="first">Submit images for classification</p> +<li><p>Submit images for classification</p> <div class="highlight-default notranslate"><div class="highlight"><pre><span></span> $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api $ curl -i -F [email protected] http://localhost:9999/api @@ -330,15 +248,6 @@ to SINGA for image classification.</p> </div> <footer> - <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> - - <a href="../../../../downloads.html" class="btn btn-neutral float-right" title="Download SINGA" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a> - - - <a href="../resnet/README.html" class="btn btn-neutral float-left" title="name: Resnets on ImageNet SINGA version: 1.1 SINGA commit: 45ec92d8ffc1fa1385a9307fdf07e21da939ee2f parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/resnet-18.tar.gz license: Apache V2, https://github.com/facebook/fb.resnet.torch/blob/master/LICENSE"; 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