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| <section id="module-apache_beam.ml.inference.onnx_inference"> |
| <span id="apache-beam-ml-inference-onnx-inference-module"></span><h1>apache_beam.ml.inference.onnx_inference module<a class="headerlink" href="#module-apache_beam.ml.inference.onnx_inference" title="Link to this heading"></a></h1> |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy"> |
| <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.onnx_inference.</span></span><span class="sig-name descname"><span class="pre">OnnxModelHandlerNumpy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">model_uri:</span> <span class="pre">str,</span> <span class="pre">session_options=None,</span> <span class="pre">providers=['CUDAExecutionProvider',</span> <span class="pre">'CPUExecutionProvider'],</span> <span class="pre">provider_options=None,</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">onnxruntime.InferenceSession,</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"><function</span> <span class="pre">default_numpy_inference_fn>,</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">min_batch_size:</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_size:</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/onnx_inference.html#OnnxModelHandlerNumpy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy" 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>, <code class="xref py py-class docutils literal notranslate"><span class="pre">InferenceSession</span></code>]</p> |
| <p>Implementation of the ModelHandler interface for onnx |
| using numpy arrays as input. |
| Note that inputs to ONNXModelHandler should be of the same sizes</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">OnnxModelHandler</span><span class="p">(</span><span class="n">model_uri</span><span class="o">=</span><span class="s2">"my_uri"</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"><ul class="simple"> |
| <li><p><strong>model_uri</strong> – The URI to where the model is saved.</p></li> |
| <li><p><strong>inference_fn</strong> – The inference function to use on RunInference calls. |
| default=default_numpy_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 > 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>min_batch_size</strong> – the minimum batch size to use when batching inputs.</p></li> |
| <li><p><strong>max_batch_size</strong> – the maximum batch size to use when batching inputs.</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> – ‘env_vars’ can be used to set environment variables |
| before loading the model.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.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">→</span> <span class="sig-return-typehint"><span class="pre">onnxruntime.InferenceSession</span></span></span><a class="reference internal" href="_modules/apache_beam/ml/inference/onnx_inference.html#OnnxModelHandlerNumpy.load_model"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.load_model" title="Link to this definition"></a></dt> |
| <dd><p>Loads and initializes an onnx inference session for processing.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.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">inference_session</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">onnxruntime.InferenceSession</span></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">→</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/onnx_inference.html#OnnxModelHandlerNumpy.run_inference"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.run_inference" title="Link to this definition"></a></dt> |
| <dd><p>Runs inferences on a batch of numpy arrays.</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 sequence of examples as numpy arrays. They should |
| be single examples.</p></li> |
| <li><p><strong>inference_session</strong> – An onnx inference session. |
| Must be runnable with input x where x is sequence of numpy array</p></li> |
| <li><p><strong>inference_args</strong> – Any additional arguments for an inference.</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.onnx_inference.OnnxModelHandlerNumpy.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">→</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/onnx_inference.html#OnnxModelHandlerNumpy.get_num_bytes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.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.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.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">→</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/onnx_inference.html#OnnxModelHandlerNumpy.get_metrics_namespace"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.get_metrics_namespace" 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>A namespace for metrics collected by the RunInference transform.</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.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">→</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/onnx_inference.html#OnnxModelHandlerNumpy.share_model_across_processes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.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.onnx_inference.OnnxModelHandlerNumpy.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">→</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/onnx_inference.html#OnnxModelHandlerNumpy.model_copies"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.model_copies" 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.onnx_inference.OnnxModelHandlerNumpy.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> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/collections.abc.html#collections.abc.Mapping" title="(in Python v3.13)"><span class="pre">Mapping</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></span><a class="reference internal" href="_modules/apache_beam/ml/inference/onnx_inference.html#OnnxModelHandlerNumpy.batch_elements_kwargs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.ml.inference.onnx_inference.OnnxModelHandlerNumpy.batch_elements_kwargs" title="Link to this definition"></a></dt> |
| <dd></dd></dl> |
| |
| </dd></dl> |
| |
| </section> |
| |
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