vpruthi/doc-exports
1
0
Fork 0
forked from docs/doc-exports
Code Pull Requests Activity
doc-exports/docs/modelarts/sdk-ref/modelarts_04_0131.html
Lai, Weijian eebf6cb7fa modelarts_sdk-ref_20230504 
Reviewed-by: Jiang, Beibei <beibei.jiang@t-systems.com>
Co-authored-by: Lai, Weijian <laiweijian4@huawei.com>
Co-committed-by: Lai, Weijian <laiweijian4@huawei.com>
2023-05-11 09:58:56 +00:00

358 lines
42 KiB
HTML
Raw Blame History

<a name="modelarts_04_0131"></a><a name="modelarts_04_0131"></a>
<h1 class="topictitle1">Creating a Training Job</h1>
<div id="body8662426"><p id="modelarts_04_0131__en-us_topic_0180094052_p642231880">If a training job failed on the training platform, view detailed logs on the platform or by calling the API in <a href="modelarts_04_0164.html">Obtaining Training Job Logs</a>.</p>
<div class="section" id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_section20261580353"><h4 class="sectiontitle">Sample Code</h4><p id="modelarts_04_0131__en-us_topic_0180094052_p1641654720415">In ModelArts notebook, you do not need to enter authentication parameters for session authentication. For details about session authentication of other development environments, see <a href="modelarts_04_0123.html">Session Authentication</a>.</p>
<ul id="modelarts_04_0131__en-us_topic_0180094052_ul1415931516913"><li id="modelarts_04_0131__en-us_topic_0180094052_li1415918154918">Example 1: Create a training job using the data stored on OBS.<div class="codecoloring" codetype="Python" id="modelarts_04_0131__en-us_topic_0180094052_screen10900450672"><div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span class="normal"> 1</span>
<span class="normal"> 2</span>
<span class="normal"> 3</span>
<span class="normal"> 4</span>
<span class="normal"> 5</span>
<span class="normal"> 6</span>
<span class="normal"> 7</span>
<span class="normal"> 8</span>
<span class="normal"> 9</span>
<span class="normal">10</span>
<span class="normal">11</span>
<span class="normal">12</span>
<span class="normal">13</span>
<span class="normal">14</span>
<span class="normal">15</span>
<span class="normal">16</span>
<span class="normal">17</span>
<span class="normal">18</span>
<span class="normal">19</span>
<span class="normal">20</span>
<span class="normal">21</span></pre></div></td><td class="code"><div><pre><span></span><span class="kn">from</span> <span class="nn">modelarts.session</span> <span class="kn">import</span> <span class="n">Session</span>
<span class="kn">from</span> <span class="nn">modelarts.estimator</span> <span class="kn">import</span> <span class="n">Estimator</span>
<span class="n">session</span> <span class="o">=</span> <span class="n">Session</span><span class="p">()</span>
<span class="n">estimator</span> <span class="o">=</span> <span class="n">Estimator</span><span class="p">(</span>
<span class="n">modelarts_session</span><span class="o">=</span><span class="n">session</span><span class="p">,</span>
<span class="n">framework_type</span><span class="o">=</span><span class="s1">'PyTorch'</span><span class="p">,</span> <span class="c1"># AI engine name</span>
<span class="n">framework_version</span><span class="o">=</span><span class="s1">'PyTorch-1.0.0-python3.6'</span><span class="p">,</span> <span class="c1"># AI engine version</span>
<span class="n">code_dir</span><span class="o">=</span><span class="s1">'/bucket/src/'</span><span class="p">,</span> <span class="c1"># Training script directory</span>
<span class="n">boot_file</span><span class="o">=</span><span class="s1">'/bucket/src/pytorch_sentiment.py'</span><span class="p">,</span> <span class="c1"># Training boot script directory</span>
<span class="n">log_url</span><span class="o">=</span><span class="s1">'/bucket/log/'</span><span class="p">,</span> <span class="c1"># Training log directory</span>
<span class="n">hyperparameters</span><span class="o">=</span><span class="p">[</span>
<span class="p">{</span><span class="s2">&quot;label&quot;</span><span class="p">:</span><span class="s2">&quot;classes&quot;</span><span class="p">,</span>
<span class="s2">&quot;value&quot;</span><span class="p">:</span> <span class="s2">&quot;10&quot;</span><span class="p">},</span>
<span class="p">{</span><span class="s2">&quot;label&quot;</span><span class="p">:</span><span class="s2">&quot;lr&quot;</span><span class="p">,</span>
<span class="s2">&quot;value&quot;</span><span class="p">:</span> <span class="s2">&quot;0.001&quot;</span><span class="p">}</span>
<span class="p">],</span>
<span class="n">output_path</span><span class="o">=</span><span class="s1">'/bucket/output/'</span><span class="p">,</span> <span class="c1"># Training output directory</span>
<span class="n">train_instance_type</span><span class="o">=</span><span class="s1">'modelarts.vm.cpu.2u'</span><span class="p">,</span> <span class="c1"># Training environment flavor</span>
<span class="n">train_instance_count</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="c1"># Number of training nodes</span>
<span class="n">job_description</span><span class="o">=</span><span class="s1">'pytorch-sentiment with ModelArts SDK'</span><span class="p">)</span> <span class="c1"># Training job description</span>
<span class="n">job_instance</span> <span class="o">=</span> <span class="n">estimator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">inputs</span><span class="o">=</span><span class="s1">'/bucket/data/train/'</span><span class="p">,</span> <span class="n">wait</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">job_name</span><span class="o">=</span><span class="s1">'my_training_job'</span><span class="p">)</span>
</pre></div></td></tr></table></div>
</div>
</li></ul>
<ul id="modelarts_04_0131__en-us_topic_0180094052_ul484182413916"><li id="modelarts_04_0131__en-us_topic_0180094052_li484424199">Example 2: Create a training job using a dataset.<div class="codecoloring" codetype="Python" id="modelarts_04_0131__en-us_topic_0180094052_screen68711580815"><div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span class="normal"> 1</span>
<span class="normal"> 2</span>
<span class="normal"> 3</span>
<span class="normal"> 4</span>
<span class="normal"> 5</span>
<span class="normal"> 6</span>
<span class="normal"> 7</span>
<span class="normal"> 8</span>
<span class="normal"> 9</span>
<span class="normal">10</span>
<span class="normal">11</span>
<span class="normal">12</span>
<span class="normal">13</span>
<span class="normal">14</span>
<span class="normal">15</span>
<span class="normal">16</span>
<span class="normal">17</span>
<span class="normal">18</span>
<span class="normal">19</span>
<span class="normal">20</span>
<span class="normal">21</span></pre></div></td><td class="code"><div><pre><span></span><span class="kn">from</span> <span class="nn">modelarts.session</span> <span class="kn">import</span> <span class="n">Session</span>
<span class="kn">from</span> <span class="nn">modelarts.estimator</span> <span class="kn">import</span> <span class="n">Estimator</span>
<span class="n">session</span> <span class="o">=</span> <span class="n">Session</span><span class="p">()</span>
<span class="n">estimator</span> <span class="o">=</span> <span class="n">Estimator</span><span class="p">(</span>
<span class="n">modelarts_session</span><span class="o">=</span><span class="n">session</span><span class="p">,</span>
<span class="n">framework_type</span><span class="o">=</span><span class="s1">'PyTorch'</span><span class="p">,</span> <span class="c1"># AI engine name</span>
<span class="n">framework_version</span><span class="o">=</span><span class="s1">'PyTorch-1.0.0-python3.6'</span><span class="p">,</span> <span class="c1"># AI engine version</span>
<span class="n">code_dir</span><span class="o">=</span><span class="s1">'/bucket/src/'</span><span class="p">,</span> <span class="c1"># Training script directory</span>
<span class="n">boot_file</span><span class="o">=</span><span class="s1">'/bucket/src/pytorch_sentiment.py'</span><span class="p">,</span> <span class="c1"># Training boot script directory</span>
<span class="n">log_url</span><span class="o">=</span><span class="s1">'/bucket/log/'</span><span class="p">,</span> <span class="c1"># Training log directory</span>
<span class="n">hyperparameters</span><span class="o">=</span><span class="p">[</span>
<span class="p">{</span><span class="s2">&quot;label&quot;</span><span class="p">:</span><span class="s2">&quot;classes&quot;</span><span class="p">,</span>
<span class="s2">&quot;value&quot;</span><span class="p">:</span> <span class="s2">&quot;10&quot;</span><span class="p">},</span>
<span class="p">{</span><span class="s2">&quot;label&quot;</span><span class="p">:</span><span class="s2">&quot;lr&quot;</span><span class="p">,</span>
<span class="s2">&quot;value&quot;</span><span class="p">:</span> <span class="s2">&quot;0.001&quot;</span><span class="p">}</span>
<span class="p">],</span>
<span class="n">output_path</span><span class="o">=</span><span class="s1">'/bucket/output/'</span><span class="p">,</span> <span class="c1"># Training output directory</span>
<span class="n">train_instance_type</span><span class="o">=</span><span class="s1">'modelarts.vm.cpu.2u'</span><span class="p">,</span> <span class="c1"># Training environment flavor</span>
<span class="n">train_instance_count</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="c1"># Number of training nodes</span>
<span class="n">job_description</span><span class="o">=</span><span class="s1">'pytorch-sentiment with ModelArts SDK'</span><span class="p">)</span> <span class="c1"># Training job description</span>
<span class="n">job_instance</span> <span class="o">=</span> <span class="n">estimator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">dataset_id</span><span class="o">=</span><span class="s1">'your_dataset_id'</span><span class="p">,</span> <span class="n">dataset_version_id</span><span class="o">=</span><span class="s1">'your_dataset_version_id'</span><span class="p">,</span> <span class="n">wait</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">job_name</span><span class="o">=</span><span class="s1">'my_training_job'</span><span class="p">)</span>
</pre></div></td></tr></table></div>
</div>
</li><li id="modelarts_04_0131__en-us_topic_0180094052_li1267163919570">Example 3: Create a training job using a custom image.<div class="codecoloring" codetype="Python" id="modelarts_04_0131__en-us_topic_0180094052_screen2671939115712"><div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span class="normal"> 1</span>
<span class="normal"> 2</span>
<span class="normal"> 3</span>
<span class="normal"> 4</span>
<span class="normal"> 5</span>
<span class="normal"> 6</span>
<span class="normal"> 7</span>
<span class="normal"> 8</span>
<span class="normal"> 9</span>
<span class="normal">10</span>
<span class="normal">11</span>
<span class="normal">12</span>
<span class="normal">13</span>
<span class="normal">14</span>
<span class="normal">15</span>
<span class="normal">16</span>
<span class="normal">17</span>
<span class="normal">18</span>
<span class="normal">19</span></pre></div></td><td class="code"><div><pre><span></span><span class="kn">from</span> <span class="nn">modelarts.session</span> <span class="kn">import</span> <span class="n">Session</span>
<span class="kn">from</span> <span class="nn">modelarts.estimator</span> <span class="kn">import</span> <span class="n">Estimator</span>
<span class="n">session</span> <span class="o">=</span> <span class="n">Session</span><span class="p">()</span>
<span class="n">estimator</span> <span class="o">=</span> <span class="n">Estimator</span><span class="p">(</span>
<span class="n">modelarts_session</span><span class="o">=</span><span class="n">session</span><span class="p">,</span>
<span class="n">log_url</span><span class="o">=</span><span class="s1">'/bucket/log/'</span><span class="p">,</span> <span class="c1"># Training log directory</span>
<span class="n">hyperparameters</span><span class="o">=</span><span class="p">[</span>
<span class="p">{</span><span class="s2">&quot;label&quot;</span><span class="p">:</span><span class="s2">&quot;classes&quot;</span><span class="p">,</span>
<span class="s2">&quot;value&quot;</span><span class="p">:</span> <span class="s2">&quot;10&quot;</span><span class="p">},</span>
<span class="p">{</span><span class="s2">&quot;label&quot;</span><span class="p">:</span><span class="s2">&quot;lr&quot;</span><span class="p">,</span>
<span class="s2">&quot;value&quot;</span><span class="p">:</span> <span class="s2">&quot;0.001&quot;</span><span class="p">}</span>
<span class="p">],</span>
<span class="n">output_path</span><span class="o">=</span><span class="s1">'/bucket/output/'</span><span class="p">,</span> <span class="c1"># Training output directory</span>
<span class="n">train_instance_type</span><span class="o">=</span><span class="s1">'modelarts.vm.cpu.2u'</span><span class="p">,</span> <span class="c1"># Training environment flavor</span>
<span class="n">train_instance_count</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="c1"># Number of training nodes</span>
<span class="n">user_command</span><span class="o">=</span><span class="s1">'bash -x /home/work/run_train.sh python /home/work/user-job-dir/app/mnist/mnist_softmax.py --data_url /home/work/user-job-dir/app/mnist_data'</span><span class="p">,</span> <span class="c1"># Boot command of the custom image</span>
<span class="n">user_image_url</span><span class="o">=</span><span class="s1">'100.125.5.235:20202/jobmng/cpu-base:1.0'</span><span class="p">,</span> <span class="c1"># Address for downloading the custom image</span>
<span class="n">job_description</span><span class="o">=</span><span class="s1">'pytorch-sentiment with ModelArts SDK'</span><span class="p">)</span> <span class="c1"># Training job description</span>
<span class="n">job_instance</span> <span class="o">=</span> <span class="n">estimator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">inputs</span><span class="o">=</span><span class="s1">'/bucket/data/train/'</span><span class="p">,</span> <span class="n">wait</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">job_name</span><span class="o">=</span><span class="s1">'my_training_job'</span><span class="p">)</span>
</pre></div></td></tr></table></div>
</div>
</li></ul>
</div>
<div class="section" id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_section4735195219416"><h4 class="sectiontitle">Parameter Description</h4>
<div class="tablenoborder"><table cellpadding="4" cellspacing="0" summary="" id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_table155461191218" frame="border" border="1" rules="all"><caption><b>Table 1 </b>Estimator request parameters</caption><thead align="left"><tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row254817912212"><th align="left" class="cellrowborder" valign="top" width="14.85148514851485%" id="mcps1.3.3.2.2.5.1.1"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p12549899214">Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="11.881188118811881%" id="mcps1.3.3.2.2.5.1.2"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p3552101193813">Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="9.900990099009901%" id="mcps1.3.3.2.2.5.1.3"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1755169172118">Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="63.366336633663366%" id="mcps1.3.3.2.2.5.1.4"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p55521998211">Description</p>
</th>
</tr>
</thead>
<tbody><tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row8893215413"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p6891421842">modelarts_session</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p68972047">Yes</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p158912219419">Object</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1689152543">Session object. For details about the initialization method, see <a href="modelarts_04_0123.html">Session Authentication</a>.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row197933582219"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p25545912114">train_instance_count</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p955361173817">Yes</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p55561095217">Long</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p25573982112">Number of compute nodes in a training job</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row105532902114"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p115007506428">code_dir</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p4553121118384">No</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1750655034220">String</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p750985094216">Code directory of a training job, for example, <span class="filepath" id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_filepath1951216503429"><b>/bucket/src/</b></span>. Leave this parameter blank when <strong id="modelarts_04_0131__en-us_topic_0180094052_b8293184620402">model_name</strong> is set.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row164861109396"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p35209501423">boot_file</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1955318112388">No</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p552245012421">String</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1052817508427">Boot file of a training job, which needs to be stored in the code directory. For example, <span class="filepath" id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_filepath953055064213"><b>/bucket/src/boot.py</b></span>. Leave this parameter blank when <strong id="modelarts_04_0131__en-us_topic_0180094052_b887484618410">model_name</strong> is set.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row1390105335719"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p7801836172112">output_path</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p95531511163817">Yes</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p12801133632113">String</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p880183622110">Output path of a training job</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row3799183612114"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p13562119132119">hyperparameters</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p655755054219">No</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1756418919215">JSON Array</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1956514920216">Running parameters of a training job. It is a collection of label-value pairs of the string type. This parameter is a container environment variable when a job uses a custom image. For details about hyperparameters if a built-in algorithm is used, see <a href="https://docs.otc.t-systems.com/modelarts/umn/training_management/built-in_algorithms/algorithms_and_their_running_parameters.html#modelarts-23-0158" target="_blank" rel="noopener noreferrer">Algorithms and Their Running Parameters</a>.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row83521247152016"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p106881050154220">log_url</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p17806757142413">No</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1369555013425">String</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p9699950194211">OBS URL of the logs of a training job. By default, this parameter is left blank. Example value: <span class="filepath" id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_filepath770045019429"><b>/usr/log/</b></span></p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row1912536142111"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p109129363215">train_instance_type</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p555331113819">Yes</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p291283612219">Long</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p199131536192118">Resource flavor selected for a training job. If you choose to train on the training platform, obtain the value by calling the API described in <a href="modelarts_04_0191.html">Obtaining Resource Flavors</a>.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row13142103743519"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p2014213371353">framework_type</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p16553201143810">No</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1014217373359">String</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p565095012422">Engine selected for a training job. Obtain the value by calling the API described in <a href="modelarts_04_0192.html">Obtaining Engine Types</a>. Leave this parameter blank when <strong id="modelarts_04_0131__en-us_topic_0180094052_b186510431927">model_name</strong> is set.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row192212012216"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1822211112118">framework_version</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1722201162119">No</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p142221612219">String</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p6270941135920">Engine version selected for a training job. Obtain the value by calling the API described in <a href="modelarts_04_0192.html">Obtaining Engine Types</a>. Leave this parameter blank when <strong id="modelarts_04_0131__en-us_topic_0180094052_b16677850165816">model_name</strong> is set.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row9499151142612"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p12675171136">job_description</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p196751771039">No</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p8675972311">String</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1767517712315">Description of a training job</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row49082484413"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p255514164311">user_image_url</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p5555144113435">No</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p5555841114318">String</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p755554118434">SWR URL of the custom image used by a training job. Example value: <span class="filepath" id="modelarts_04_0131__en-us_topic_0180094052_filepath18497164091018"><b>100.125.5.235:20202/jobmng/custom-cpu-base:1.0</b></span></p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row19129155110419"><td class="cellrowborder" valign="top" width="14.85148514851485%" headers="mcps1.3.3.2.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p46411034174620">user_command</p>
</td>
<td class="cellrowborder" valign="top" width="11.881188118811881%" headers="mcps1.3.3.2.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p11641434154610">No</p>
</td>
<td class="cellrowborder" valign="top" width="9.900990099009901%" headers="mcps1.3.3.2.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1364113434619">String</p>
</td>
<td class="cellrowborder" valign="top" width="63.366336633663366%" headers="mcps1.3.3.2.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p17641113410465">Boot command used to start the container of the custom image of a training job. The format is <span class="filepath" id="modelarts_04_0131__en-us_topic_0180094052_filepath9183749121013"><b>bash /home/work/run_train.sh python /home/work/user-job-dir/app/train.py {python_file_parameter}</b></span>.</p>
</td>
</tr>
</tbody>
</table>
</div>
<div class="tablenoborder"><table cellpadding="4" cellspacing="0" summary="" id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_table51828155712" frame="border" border="1" rules="all"><caption><b>Table 2 </b><strong id="modelarts_04_0131__en-us_topic_0180094052_b1473202314">fit</strong> request parameters</caption><thead align="left"><tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row4182201512718"><th align="left" class="cellrowborder" valign="top" width="15%" id="mcps1.3.3.3.2.5.1.1"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p4182161520719">Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="12%" id="mcps1.3.3.3.2.5.1.2"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1718210151276">Mandatory</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="10%" id="mcps1.3.3.3.2.5.1.3"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p418215153719">Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="63%" id="mcps1.3.3.3.2.5.1.4"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p20182101511716">Description</p>
</th>
</tr>
</thead>
<tbody><tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row131833158713"><td class="cellrowborder" valign="top" width="15%" headers="mcps1.3.3.3.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p19658036152118">inputs</p>
</td>
<td class="cellrowborder" valign="top" width="12%" headers="mcps1.3.3.3.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p2553411163815">Yes</p>
</td>
<td class="cellrowborder" valign="top" width="10%" headers="mcps1.3.3.3.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p465883632119">String</p>
</td>
<td class="cellrowborder" valign="top" width="63%" headers="mcps1.3.3.3.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_p684343891119">Data storage location of a training job.</p>
<p id="modelarts_04_0131__en-us_topic_0180094052_p183401941161113"><strong id="modelarts_04_0131__en-us_topic_0180094052_b630713417226">inputs</strong> cannot be used with <strong id="modelarts_04_0131__en-us_topic_0180094052_b230914111224">dataset_id</strong> and <strong id="modelarts_04_0131__en-us_topic_0180094052_b1310144112215">dataset_version_id</strong>, or with <strong id="modelarts_04_0131__en-us_topic_0180094052_b153115415220">data_source</strong> at the same time. However, one of the parameters must exist.</p>
<p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p765843622116">Only this parameter is supported in local training.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row1458104910441"><td class="cellrowborder" valign="top" width="15%" headers="mcps1.3.3.3.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1857315014211">dataset_id</p>
</td>
<td class="cellrowborder" valign="top" width="12%" headers="mcps1.3.3.3.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p455341112382">No</p>
</td>
<td class="cellrowborder" valign="top" width="10%" headers="mcps1.3.3.3.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p6578165015427">String</p>
</td>
<td class="cellrowborder" valign="top" width="63%" headers="mcps1.3.3.3.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_p1938131084614">Dataset ID of a training job. To obtain the dataset ID, <a href="https://docs.otc.t-systems.com/modelarts/umn/data_management/managing_dataset_versions.html" target="_blank" rel="noopener noreferrer">Managing Dataset Versions</a>.</p>
<p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p9583950184210">This parameter must be used together with <strong id="modelarts_04_0131__en-us_topic_0180094052_b0705134214015">dataset_version_id</strong>, but cannot be used together with <strong id="modelarts_04_0131__en-us_topic_0180094052_b12705742114011">inputs</strong>.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row26141951154417"><td class="cellrowborder" valign="top" width="15%" headers="mcps1.3.3.3.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p18589165044211">dataset_version_id</p>
</td>
<td class="cellrowborder" valign="top" width="12%" headers="mcps1.3.3.3.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1755351183816">No</p>
</td>
<td class="cellrowborder" valign="top" width="10%" headers="mcps1.3.3.3.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p16592155011420">String</p>
</td>
<td class="cellrowborder" valign="top" width="63%" headers="mcps1.3.3.3.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_p28595368112">Dataset version ID of a training job. To obtain the dataset version ID, <a href="https://docs.otc.t-systems.com/modelarts/umn/data_management/managing_dataset_versions.html" target="_blank" rel="noopener noreferrer">Managing Dataset Versions</a>.</p>
<p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p205997508422">This parameter must be used together with <strong id="modelarts_04_0131__en-us_topic_0180094052_b1244193991211">dataset_id</strong>, but cannot be used together with <strong id="modelarts_04_0131__en-us_topic_0180094052_b16441203931215">inputs</strong>.</p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row1418310152720"><td class="cellrowborder" valign="top" width="15%" headers="mcps1.3.3.3.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1118312155718">wait</p>
</td>
<td class="cellrowborder" valign="top" width="12%" headers="mcps1.3.3.3.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1718314155717">No</p>
</td>
<td class="cellrowborder" valign="top" width="10%" headers="mcps1.3.3.3.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p14183815772">Boolean</p>
</td>
<td class="cellrowborder" valign="top" width="63%" headers="mcps1.3.3.3.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p10183111513712">Whether to wait for the completion of a training job. Default value: <strong id="modelarts_04_0131__en-us_topic_0180094052_b61671119111315">False</strong></p>
</td>
</tr>
<tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row31833151071"><td class="cellrowborder" valign="top" width="15%" headers="mcps1.3.3.3.2.5.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p141831715277">job_name</p>
</td>
<td class="cellrowborder" valign="top" width="12%" headers="mcps1.3.3.3.2.5.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p918319159717">No</p>
</td>
<td class="cellrowborder" valign="top" width="10%" headers="mcps1.3.3.3.2.5.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p818316151671">String</p>
</td>
<td class="cellrowborder" valign="top" width="63%" headers="mcps1.3.3.3.2.5.1.4 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p1218315151575">Name of a training job, consisting of 1 to 64 alphanumeric characters. If this parameter is left blank, a job name is generated randomly.</p>
</td>
</tr>
</tbody>
</table>
</div>
<div class="tablenoborder"><table cellpadding="4" cellspacing="0" summary="" id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_table973120224596" frame="border" border="1" rules="all"><caption><b>Table 3 </b>Parameters in the successful response to training</caption><thead align="left"><tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row2731522195910"><th align="left" class="cellrowborder" valign="top" width="14.705882352941178%" id="mcps1.3.3.4.2.4.1.1"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p57306225598">Parameter</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="12.745098039215685%" id="mcps1.3.3.4.2.4.1.2"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p117308225593">Type</p>
</th>
<th align="left" class="cellrowborder" valign="top" width="72.54901960784314%" id="mcps1.3.3.4.2.4.1.3"><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p2730132255915">Description</p>
</th>
</tr>
</thead>
<tbody><tr id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_row1873172215912"><td class="cellrowborder" valign="top" width="14.705882352941178%" headers="mcps1.3.3.4.2.4.1.1 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p4731322145919">TrainingJob</p>
</td>
<td class="cellrowborder" valign="top" width="12.745098039215685%" headers="mcps1.3.3.4.2.4.1.2 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p117311922115916">Object</p>
</td>
<td class="cellrowborder" valign="top" width="72.54901960784314%" headers="mcps1.3.3.4.2.4.1.3 "><p id="modelarts_04_0131__en-us_topic_0180094052_en-us_topic_0160436006_p6731182225914">Training object. This object contains attributes such as <strong id="modelarts_04_0131__en-us_topic_0180094052_b129471359312">job_id</strong> and <strong id="modelarts_04_0131__en-us_topic_0180094052_b1948555319">version_id</strong>, and operations on a training job, such as querying, modifying, or deleting the training job. For example, you can use <strong id="modelarts_04_0131__en-us_topic_0180094052_b6948205113114">job_instance.job_id</strong> to obtain the ID of a training job.</p>
</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
<div>
<div class="familylinks">
<div class="parentlink"><strong>Parent topic:</strong> <a href="modelarts_04_0158.html">Training Jobs</a></div>
</div>
</div>
View Git Blame Copy Permalink