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‎docfx/api/TensorFlow/TensorFlow.TFGraph.yml‎

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- TensorFlowSharp
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namespace: TensorFlow
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summary: Import a serialized graph held in a byte array into this graph, using the specified import options.
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remarks: If you are tryig to load a file stored using the SavedModel file format, you should use the <xref href="TensorFlow.TFSession.FromSavedModel"></xref> API instead.
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syntax:
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content: public void Import (byte[] buffer, TensorFlow.TFImportGraphDefOptions options, TensorFlow.TFStatus status = null);
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parameters:
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- TensorFlowSharp
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namespace: TensorFlow
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summary: Imports a graph serialized into the graph
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remarks: If you are tryig to load a file stored using the SavedModel file format, you should use the <xref href="TensorFlow.TFSession.FromSavedModel"></xref> API instead.
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syntax:
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content: public void ImportGraphDef (TensorFlow.TFBuffer graphDef, TensorFlow.TFImportGraphDefOptions options, TensorFlow.TFOutput[] returnOutputs, TensorFlow.TFStatus status = null);
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parameters:

‎docfx/api/TensorFlow/TensorFlow.TFSession.yml‎

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assemblies:
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- TensorFlowSharp
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namespace: TensorFlow
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summary: Creates a session and graph from a saved session model
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summary: Creates a session and graph from a model stored in the SavedModel file format.
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remarks: >-
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This function creates a new session using the specified <code>sessionOptions</code> and then initializes
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the state (restoring tensors and other assets) using <code>runOptions</code>
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<p>
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This function creates a new session using the specified <code>sessionOptions</code> and then initializes
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the state (restoring tensors and other assets) using <code>runOptions</code>.
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</p>
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<p>
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This function loads the data that was saved using the SavedModel file format, as described
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here: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/saved_model/README.md
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</p>
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syntax:
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content: public TensorFlow.TFSession FromSavedModel (TensorFlow.TFSessionOptions sessionOptions, TensorFlow.TFBuffer runOptions, string exportDir, string[] tags, TensorFlow.TFGraph graph, TensorFlow.TFBuffer metaGraphDef, TensorFlow.TFStatus status = null);
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parameters:

‎docs/api/TensorFlow/TensorFlow.TFGraph.html‎

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</tr>
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</tbody>
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</table>
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<h5 id="TensorFlow_TFGraph_Import_System_Byte___TensorFlow_TFImportGraphDefOptions_TensorFlow_TFStatus__remarks">Remarks</h5>
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<div class="markdown level1 remarks"><p>If you are tryig to load a file stored using the SavedModel file format, you should use the <span class="xref">TensorFlow.TFSession.FromSavedModel</span> API instead.</p>
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</div>
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<a id="TensorFlow_TFGraph_Import_" data-uid="TensorFlow.TFGraph.Import*"></a>
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</tr>
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</tbody>
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</table>
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<h5 id="TensorFlow_TFGraph_ImportGraphDef_TensorFlow_TFBuffer_TensorFlow_TFImportGraphDefOptions_TensorFlow_TFOutput___TensorFlow_TFStatus__remarks">Remarks</h5>
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<div class="markdown level1 remarks"><p>If you are tryig to load a file stored using the SavedModel file format, you should use the <span class="xref">TensorFlow.TFSession.FromSavedModel</span> API instead.</p>
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</div>
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<a id="TensorFlow_TFGraph_InitializeTable_" data-uid="TensorFlow.TFGraph.InitializeTable*"></a>

‎docs/api/TensorFlow/TensorFlow.TFSession.html‎

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<a id="TensorFlow_TFSession_FromSavedModel_" data-uid="TensorFlow.TFSession.FromSavedModel*"></a>
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<h4 id="TensorFlow_TFSession_FromSavedModel_TensorFlow_TFSessionOptions_TensorFlow_TFBuffer_System_String_System_String___TensorFlow_TFGraph_TensorFlow_TFBuffer_TensorFlow_TFStatus_" data-uid="TensorFlow.TFSession.FromSavedModel(TensorFlow.TFSessionOptions,TensorFlow.TFBuffer,System.String,System.String[],TensorFlow.TFGraph,TensorFlow.TFBuffer,TensorFlow.TFStatus)">FromSavedModel(TFSessionOptions, TFBuffer, String, String[], TFGraph, TFBuffer, TFStatus)</h4>
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<div class="markdown level1 summary"><p>Creates a session and graph from a saved session model</p>
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<div class="markdown level1 summary"><p>Creates a session and graph from a model stored in the SavedModel file format.</p>
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</div>
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<div class="markdown level1 conceptual"></div>
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<h5 class="decalaration">Declaration</h5>
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</tbody>
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</table>
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<h5 id="TensorFlow_TFSession_FromSavedModel_TensorFlow_TFSessionOptions_TensorFlow_TFBuffer_System_String_System_String___TensorFlow_TFGraph_TensorFlow_TFBuffer_TensorFlow_TFStatus__remarks">Remarks</h5>
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<div class="markdown level1 remarks"><p>This function creates a new session using the specified <code>sessionOptions</code> and then initializes
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the state (restoring tensors and other assets) using <code>runOptions</code></p>
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</div>
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<div class="markdown level1 remarks"><p>
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This function creates a new session using the specified <code>sessionOptions</code> and then initializes
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the state (restoring tensors and other assets) using <code>runOptions</code>.
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</p>
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<p>
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This function loads the data that was saved using the SavedModel file format, as described
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here: <a href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/saved_model/README.md">https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/saved_model/README.md</a>
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</p></div>
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<a id="TensorFlow_TFSession_GetRunner_" data-uid="TensorFlow.TFSession.GetRunner*"></a>

‎docs/manifest.json‎

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‎ecmadocs/en/TensorFlow/TFGraph.xml‎

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Import a serialized graph held in a byte array into this graph, using the specified import options.
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</summary>
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<returns>The import.</returns>
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<remarks>To be added.</remarks>
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<remarks>
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If you are tryig to load a file stored using the SavedModel file format, you should use the <see cref="T:TensorFlow.TFSession.FromSavedModel" /> API instead.
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</remarks>
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</Docs>
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</Member>
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<Member MemberName="Import">
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<summary>
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Imports a graph serialized into the graph
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</summary>
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<remarks>To be added.</remarks>
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<remarks>
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If you are tryig to load a file stored using the SavedModel file format, you should use the <see cref="T:TensorFlow.TFSession.FromSavedModel" /> API instead.
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</remarks>
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</Docs>
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</Member>
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<Member MemberName="InitializeTable">

‎ecmadocs/en/TensorFlow/TFSession.xml‎

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<param name="metaGraphDef">On success, this will be populated on return with the contents of the MetaGraphDef (can be null).</param>
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<param name="status">Status buffer, if specified a status code will be left here, if not specified, a <see cref="T:TensorFlow.TFException" /> exception is raised if there is an error.</param>
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<summary>
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Creates a session and graph from a saved session model
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Creates a session and graph from a model stored in the SavedModel file format.
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</summary>
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<returns>On success, this populates the provided <paramref name="graph" /> with the contents of the graph stored in the specified model and <paramref name="metaGraphDef" /> with the MetaGraphDef of the loaded model.</returns>
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<remarks>
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<para>
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This function creates a new session using the specified <paramref name="sessionOptions" /> and then initializes
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the state (restoring tensors and other assets) using <paramref name="runOptions" /></remarks>
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the state (restoring tensors and other assets) using <paramref name="runOptions" />.
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</para>
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<para>
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This function loads the data that was saved using the SavedModel file format, as described
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here: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/saved_model/README.md
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</para>
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</remarks>
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</Docs>
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</Member>
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<Member MemberName="GetRunner">

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