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| <h1 class="post-title">Examine forward results with hooks</h1> |
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| |
| <h1 id="examine-forward-results-with-hooks">Examine forward results with hooks</h1> |
| |
| <p>There are currently three ways to register a function in an MXNet Gluon Block for execution:</p> |
| |
| <ul> |
| <li>before <code class="highlighter-rouge">forward</code> via <a href="/api/python/docs/api/gluon/block.html#mxnet.gluon.Block.register_forward_pre_hook">register_forward_pre_hook</a></li> |
| <li>after <code class="highlighter-rouge">forward</code> via <a href="/api/python/docs/api/gluon/block.html#mxnet.gluon.Block.register_forward_hook">register_forward_hook</a></li> |
| <li>as a callback via <a href="/api/python/docs/api/gluon/block.html#mxnet.gluon.Block.register_op_hook">register_op_hook</a></li> |
| </ul> |
| |
| <h2 id="pre-forward-hook">Pre-forward hook</h2> |
| |
| <p>To register a hook prior to forward execution, the requirement is that the registered operation <strong>should not modify the input or output</strong>. For example: <code class="highlighter-rouge">hook(block, input) -> None</code>. This is useful to get a summary before execution.</p> |
| |
| <div class="highlighter-rouge"><div class="highlight"><pre class="highlight"><code>import mxnet as mx |
| from mxnet.gluon import nn |
| |
| block = nn.Dense(10) |
| block.initialize() |
| print("{}".format(block)) |
| # Dense(None -> 10, linear) |
| |
| def pre_hook(block, input) -> None: # notice it has two arguments, one block and one input |
| print("{}".format(block)) |
| return |
| |
| # register |
| pre_handle = block.register_forward_pre_hook(pre_hook) |
| input = mx.nd.ones((3, 5)) |
| print(block(input)) |
| |
| # Dense(None -> 10, linear) |
| # [[ 0.11254273 0.11162187 0.02200389 -0.04842059 0.09531345 0.00880495 |
| # -0.07610667 0.1562067 0.14192852 0.04463106] |
| # [ 0.11254273 0.11162187 0.02200389 -0.04842059 0.09531345 0.00880495 |
| # -0.07610667 0.1562067 0.14192852 0.04463106] |
| # [ 0.11254273 0.11162187 0.02200389 -0.04842059 0.09531345 0.00880495 |
| # -0.07610667 0.1562067 0.14192852 0.04463106]] |
| # <NDArray 3x10 @cpu(0)> |
| </code></pre></div></div> |
| |
| <p>We can <code class="highlighter-rouge">detach</code> a hook from a block:</p> |
| |
| <div class="highlighter-rouge"><div class="highlight"><pre class="highlight"><code>pre_handle.detach() |
| print(block(input)) |
| |
| # [[ 0.11254273 0.11162187 0.02200389 -0.04842059 0.09531345 0.00880495 |
| # -0.07610667 0.1562067 0.14192852 0.04463106] |
| # [ 0.11254273 0.11162187 0.02200389 -0.04842059 0.09531345 0.00880495 |
| # -0.07610667 0.1562067 0.14192852 0.04463106] |
| # [ 0.11254273 0.11162187 0.02200389 -0.04842059 0.09531345 0.00880495 |
| # -0.07610667 0.1562067 0.14192852 0.04463106]] |
| # <NDArray 3x10 @cpu(0)> |
| </code></pre></div></div> |
| |
| <p>Notice <code class="highlighter-rouge">Dense(None -> 10, linear)</code> is not displayed anymore.</p> |
| |
| <h2 id="post-forward-hook">Post-forward hook</h2> |
| |
| <p>Registering a hook after forward execution is very similar to pre-forward hook (as explained above) with the difference that the hook signature should be <code class="highlighter-rouge">hook(block, input, output) -> None</code> where <strong>hook should not modify the input and output.</strong> Continuing from the above example:</p> |
| |
| <div class="highlighter-rouge"><div class="highlight"><pre class="highlight"><code>def post_hook(block, intput, output) -> None: |
| print("{}".format(block)) |
| return |
| |
| post_handle = block.register_forward_hook(post_hook) |
| print(block(input)) |
| |
| # Dense(5 -> 10, linear) |
| # [[ 0.11254273 0.11162187 0.02200389 -0.04842059 0.09531345 0.00880495 |
| # -0.07610667 0.1562067 0.14192852 0.04463106] |
| # [ 0.11254273 0.11162187 0.02200389 -0.04842059 0.09531345 0.00880495 |
| # -0.07610667 0.1562067 0.14192852 0.04463106] |
| # [ 0.11254273 0.11162187 0.02200389 -0.04842059 0.09531345 0.00880495 |
| # -0.07610667 0.1562067 0.14192852 0.04463106]] |
| # <NDArray 3x10 @cpu(0)> |
| </code></pre></div></div> |
| |
| <p>Notice the difference between <code class="highlighter-rouge">pre_hook</code> and <code class="highlighter-rouge">post_hook</code> results due to shape inference after <code class="highlighter-rouge">forward</code> is done executing.</p> |
| |
| <h2 id="callback-hook">Callback hook</h2> |
| |
| <p>We can register a callback monitor to monitor all operators that are called by the <code class="highlighter-rouge">HybridBlock</code> <strong>after hybridization</strong> with <code class="highlighter-rouge">register_op_hook(callback, monitor_all=False) </code> where the callback signature should be:</p> |
| |
| <div class="highlighter-rouge"><div class="highlight"><pre class="highlight"><code>callback(node_name: str, opr_name: str, arr: NDArray) -> None |
| </code></pre></div></div> |
| |
| <p>where <code class="highlighter-rouge">node_name</code> is the name of the tensor being inspected (str), <code class="highlighter-rouge">opr_name</code> is the name of the operator producing or consuming that tensor (str) and <code class="highlighter-rouge">arr</code> the tensor being inspected (NDArray).</p> |
| |
| <div class="highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="n">import</span> <span class="n">mxnet</span> <span class="k">as</span> <span class="n">mx</span> |
| <span class="k">from</span> <span class="n">mxnet</span><span class="p">.</span><span class="n">gluon</span> <span class="n">import</span> <span class="n">nn</span> |
| |
| <span class="n">def</span> <span class="n">mon_callback</span><span class="p">(</span><span class="n">node_name</span><span class="p">,</span> <span class="n">opr_name</span><span class="p">,</span> <span class="n">arr</span><span class="p">):</span> |
| <span class="n">print</span><span class="p">(</span><span class="s2">"{}"</span><span class="p">.</span><span class="n">format</span><span class="p">(</span><span class="n">node_name</span><span class="p">))</span> |
| <span class="n">print</span><span class="p">(</span><span class="s2">"{}"</span><span class="p">.</span><span class="n">format</span><span class="p">(</span><span class="n">opr_name</span><span class="p">))</span> |
| <span class="n">return</span> |
| |
| <span class="k">model</span> <span class="p">=</span> <span class="n">nn</span><span class="p">.</span><span class="n">HybridSequential</span><span class="p">(</span><span class="n">prefix</span><span class="p">=</span><span class="s2">"dense_"</span><span class="p">)</span> |
| <span class="k">with</span> <span class="k">model</span><span class="p">.</span><span class="n">name_scope</span><span class="p">():</span> |
| <span class="k">model</span><span class="p">.</span><span class="n">add</span><span class="p">(</span><span class="n">mx</span><span class="p">.</span><span class="n">gluon</span><span class="p">.</span><span class="n">nn</span><span class="p">.</span><span class="n">Dense</span><span class="p">(</span><span class="m">2</span><span class="p">))</span> |
| |
| <span class="k">model</span><span class="p">.</span><span class="n">initialize</span><span class="p">()</span> |
| <span class="k">model</span><span class="p">.</span><span class="n">hybridize</span><span class="p">()</span> |
| <span class="k">model</span><span class="p">.</span><span class="n">register_op_hook</span><span class="p">(</span><span class="n">mon_callback</span><span class="p">,</span> <span class="n">monitor_all</span><span class="p">=</span><span class="nb">True</span><span class="p">)</span> |
| <span class="n">print</span><span class="p">(</span><span class="k">model</span><span class="p">(</span><span class="n">mx</span><span class="p">.</span><span class="n">nd</span><span class="p">.</span><span class="n">ones</span><span class="p">((</span><span class="m">2</span><span class="p">,</span> <span class="m">3</span><span class="p">,</span> <span class="m">4</span><span class="p">))))</span> |
| |
| <span class="p">#</span> <span class="n">b</span><span class="s1">'dense_dense0_fwd_data'</span> |
| <span class="p">#</span> <span class="n">b</span><span class="s1">'FullyConnected'</span> |
| <span class="p">#</span> <span class="n">b</span><span class="s1">'dense_dense0_fwd_weight'</span> |
| <span class="p">#</span> <span class="n">b</span><span class="s1">'FullyConnected'</span> |
| <span class="p">#</span> <span class="n">b</span><span class="s1">'dense_dense0_fwd_bias'</span> |
| <span class="p">#</span> <span class="n">b</span><span class="s1">'FullyConnected'</span> |
| <span class="p">#</span> <span class="n">b</span><span class="s1">'dense_dense0_fwd_output'</span> |
| <span class="p">#</span> <span class="n">b</span><span class="s1">'FullyConnected'</span> |
| <span class="p">#</span> <span class="p">[[-</span><span class="m">0.05979988</span> <span class="p">-</span><span class="m">0.16349721</span><span class="p">]</span> |
| <span class="p">#</span> <span class="p">[-</span><span class="m">0.05979988</span> <span class="p">-</span><span class="m">0.16349721</span><span class="p">]]</span> |
| <span class="p">#</span> <span class="p"><</span><span class="n">NDArray</span> <span class="m">2</span><span class="n">x2</span> <span class="p">@</span><span class="n">cpu</span><span class="p">(</span><span class="m">0</span><span class="p">)></span> |
| </code></pre></div></div> |
| |
| <p>Setting <code class="highlighter-rouge">monitor_all=False</code> will print only the output:</p> |
| |
| <div class="highlighter-rouge"><div class="highlight"><pre class="highlight"><code>`# b'dense_dense0_fwd_output'` |
| `# b'FullyConnected'`` |
| # [[-0.05979988 -0.16349721] |
| # [-0.05979988 -0.16349721]] |
| # <NDArray 2x2 @cpu(0)` |
| </code></pre></div></div> |
| |
| <p>Note that to get the internal operator node names, one can use <code class="highlighter-rouge">model.collect_params().items()</code>.</p> |
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