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<section id="module-apache_beam.ml.inference.tensorrt_inference">
<span id="apache-beam-ml-inference-tensorrt-inference-module"></span><h1>apache_beam.ml.inference.tensorrt_inference module<a class="headerlink" href="#module-apache_beam.ml.inference.tensorrt_inference" title="Link to this heading"></a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngine">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">apache_beam.ml.inference.tensorrt_inference.</span></span><span class="sig-name descname"><span class="pre">TensorRTEngine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">engine</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tensorrt.ICudaEngine</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngine" title="Link to this definition"></a></dt>
<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
<p>Implementation of the TensorRTEngine class which handles
allocations associated with TensorRT engine.</p>
<p>Example Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">TensorRTEngine</span><span class="p">(</span><span class="n">engine</span><span class="p">)</span>
</pre></div>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>engine</strong> – trt.ICudaEngine object that contains TensorRT engine</p>
</dd>
</dl>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngine.get_engine_attrs">
<span class="sig-name descname"><span class="pre">get_engine_attrs</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngine.get_engine_attrs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngine.get_engine_attrs" title="Link to this definition"></a></dt>
<dd><p>Returns TensorRT engine attributes.</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">apache_beam.ml.inference.tensorrt_inference.</span></span><span class="sig-name descname"><span class="pre">TensorRTEngineHandlerNumPy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">min_batch_size:</span> <span class="pre">int,</span> <span class="pre">max_batch_size:</span> <span class="pre">int,</span> <span class="pre">*,</span> <span class="pre">inference_fn:</span> <span class="pre">~collections.abc.Callable[[~collections.abc.Sequence[~numpy.ndarray],</span> <span class="pre">~apache_beam.ml.inference.tensorrt_inference.TensorRTEngine,</span> <span class="pre">dict[str,</span> <span class="pre">~typing.Any]</span> <span class="pre">|</span> <span class="pre">None],</span> <span class="pre">~collections.abc.Iterable[~apache_beam.ml.inference.base.PredictionResult]]</span> <span class="pre">=</span> <span class="pre">&lt;function</span> <span class="pre">_default_tensorRT_inference_fn&gt;,</span> <span class="pre">large_model:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False,</span> <span class="pre">model_copies:</span> <span class="pre">int</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None,</span> <span class="pre">max_batch_duration_secs:</span> <span class="pre">int</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None,</span> <span class="pre">**kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy" title="Link to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="apache_beam.ml.inference.base.html#apache_beam.ml.inference.base.ModelHandler" title="apache_beam.ml.inference.base.ModelHandler"><code class="xref py py-class docutils literal notranslate"><span class="pre">ModelHandler</span></code></a>[<a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="(in NumPy v2.3)"><code class="xref py py-class docutils literal notranslate"><span class="pre">ndarray</span></code></a>, <a class="reference internal" href="apache_beam.ml.inference.base.html#apache_beam.ml.inference.base.PredictionResult" title="apache_beam.ml.inference.base.PredictionResult"><code class="xref py py-class docutils literal notranslate"><span class="pre">PredictionResult</span></code></a>, <a class="reference internal" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngine" title="apache_beam.ml.inference.tensorrt_inference.TensorRTEngine"><code class="xref py py-class docutils literal notranslate"><span class="pre">TensorRTEngine</span></code></a>]</p>
<p>Implementation of the ModelHandler interface for TensorRT.</p>
<p>Example Usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pcoll</span> <span class="o">|</span> <span class="n">RunInference</span><span class="p">(</span>
<span class="n">TensorRTEngineHandlerNumPy</span><span class="p">(</span>
<span class="n">min_batch_size</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="n">max_batch_size</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="n">engine_path</span><span class="o">=</span><span class="s2">&quot;my_uri&quot;</span><span class="p">))</span>
</pre></div>
</div>
<p><strong>NOTE:</strong> This API and its implementation are under development and
do not provide backward compatibility guarantees.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>min_batch_size</strong> – minimum accepted batch size.</p></li>
<li><p><strong>max_batch_size</strong> – maximum accepted batch size.</p></li>
<li><p><strong>inference_fn</strong> – the inference function to use on RunInference calls.
default: _default_tensorRT_inference_fn</p></li>
<li><p><strong>large_model</strong> – set to true if your model is large enough to run into
memory pressure if you load multiple copies. Given a model that
consumes N memory and a machine with W cores and M memory, you should
set this to True if N*W &gt; M.</p></li>
<li><p><strong>model_copies</strong> – The exact number of models that you would like loaded
onto your machine. This can be useful if you exactly know your CPU or
GPU capacity and want to maximize resource utilization.</p></li>
<li><p><strong>max_batch_duration_secs</strong> – the maximum amount of time to buffer
a batch before emitting; used in streaming contexts.</p></li>
<li><p><strong>kwargs</strong> – Additional arguments like ‘engine_path’ and ‘onnx_path’ are
currently supported. ‘env_vars’ can be used to set environment variables
before loading the model.</p></li>
</ul>
</dd>
</dl>
<p>See <a class="reference external" href="https://docs.nvidia.com/deeplearning/tensorrt/api/python_api/">https://docs.nvidia.com/deeplearning/tensorrt/api/python_api/</a>
for details</p>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.batch_elements_kwargs">
<span class="sig-name descname"><span class="pre">batch_elements_kwargs</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy.batch_elements_kwargs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.batch_elements_kwargs" title="Link to this definition"></a></dt>
<dd><p>Sets min_batch_size and max_batch_size of a TensorRT engine.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.load_model">
<span class="sig-name descname"><span class="pre">load_model</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngine" title="apache_beam.ml.inference.tensorrt_inference.TensorRTEngine"><span class="pre">TensorRTEngine</span></a></span></span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy.load_model"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.load_model" title="Link to this definition"></a></dt>
<dd><p>Loads and initializes a TensorRT engine for processing.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.load_onnx">
<span class="sig-name descname"><span class="pre">load_onnx</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#tuple" title="(in Python v3.13)"><span class="pre">tuple</span></a><span class="p"><span class="pre">[</span></span><span class="pre">tensorrt.INetworkDefinition</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">tensorrt.Builder</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy.load_onnx"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.load_onnx" title="Link to this definition"></a></dt>
<dd><p>Loads and parses an onnx model for processing.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.build_engine">
<span class="sig-name descname"><span class="pre">build_engine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">network</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tensorrt.INetworkDefinition</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">builder</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tensorrt.Builder</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngine" title="apache_beam.ml.inference.tensorrt_inference.TensorRTEngine"><span class="pre">TensorRTEngine</span></a></span></span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy.build_engine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.build_engine" title="Link to this definition"></a></dt>
<dd><p>Build an engine according to parsed/created network.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.run_inference">
<span class="sig-name descname"><span class="pre">run_inference</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">batch</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Sequence" title="(in Python v3.13)"><span class="pre">Sequence</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="(in NumPy v2.3)"><span class="pre">ndarray</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">engine</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngine" title="apache_beam.ml.inference.tensorrt_inference.TensorRTEngine"><span class="pre">TensorRTEngine</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.13)"><span class="pre">dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.13)"><span class="pre">Any</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.13)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Iterable" title="(in Python v3.13)"><span class="pre">Iterable</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="apache_beam.ml.inference.base.html#apache_beam.ml.inference.base.PredictionResult" title="apache_beam.ml.inference.base.PredictionResult"><span class="pre">PredictionResult</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy.run_inference"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.run_inference" title="Link to this definition"></a></dt>
<dd><p>Runs inferences on a batch of Tensors and returns an Iterable of
TensorRT Predictions.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>batch</strong> – A np.ndarray or a np.ndarray that represents a concatenation
of multiple arrays as a batch.</p></li>
<li><p><strong>engine</strong> – A TensorRT engine.</p></li>
<li><p><strong>inference_args</strong> – Any additional arguments for an inference
that are not applicable to TensorRT.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>An Iterable of type PredictionResult.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.get_num_bytes">
<span class="sig-name descname"><span class="pre">get_num_bytes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">batch</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Sequence" title="(in Python v3.13)"><span class="pre">Sequence</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="(in NumPy v2.3)"><span class="pre">ndarray</span></a><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><span class="pre">int</span></a></span></span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy.get_num_bytes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.get_num_bytes" title="Link to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>The number of bytes of data for a batch of Tensors.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.get_metrics_namespace">
<span class="sig-name descname"><span class="pre">get_metrics_namespace</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><span class="pre">str</span></a></span></span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy.get_metrics_namespace"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.get_metrics_namespace" title="Link to this definition"></a></dt>
<dd><p>Returns a namespace for metrics collected by the RunInference transform.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.share_model_across_processes">
<span class="sig-name descname"><span class="pre">share_model_across_processes</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><span class="pre">bool</span></a></span></span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy.share_model_across_processes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.share_model_across_processes" title="Link to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.model_copies">
<span class="sig-name descname"><span class="pre">model_copies</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><span class="pre">int</span></a></span></span><a class="reference internal" href="_modules/apache_beam/ml/inference/tensorrt_inference.html#TensorRTEngineHandlerNumPy.model_copies"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.tensorrt_inference.TensorRTEngineHandlerNumPy.model_copies" title="Link to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
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