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OpDefLibrary, op_list_proto_bytes.bin
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‎README.md‎

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@@ -8,7 +8,7 @@ TensorFlow.NET is a member project of SciSharp stack.
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### How to use
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```cs
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using tf = TensorFlowNET.Core.Tensorflow;
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using TensorFlowNET.Core;
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namespace TensorFlowNET.Examples
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{

‎src/TensorFlowNET.Core/Buffer.cs‎

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using System;
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using System.Collections.Generic;
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using System.Runtime.InteropServices;
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using System.Text;
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using Tensorflow;
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namespace TensorFlowNET.Core
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{
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public class Buffer
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{
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private IntPtr _handle;
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public IntPtr Handle => _handle;
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//public TF_Buffer buffer => Marshal.PtrToStructure<TF_Buffer>(_handle);
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public unsafe Buffer()
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{
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_handle = Marshal.AllocHGlobal(sizeof(TF_Buffer));
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}
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public byte[] GetBuffer()
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{
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var buffer = Marshal.PtrToStructure<TF_Buffer>(_handle);
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var data = Marshal.AllocHGlobal(buffer.length);
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//var bytes = c_api.TF_GetBuffer(buffer.data);
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return null;
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}
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}
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}

‎src/TensorFlowNET.Core/Graph.cs‎

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@@ -32,7 +32,9 @@ public Graph(IntPtr graph)
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_names_in_use = new Dictionary<string, int>();
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}
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public unsafe Operation create_op(string op_type, object inputs, TF_DataType[] dtypes, TF_DataType[] input_types = null, Dictionary<string, AttrValue> attrs = null, string name = "Const")
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public unsafe Operation create_op(string op_type, object inputs, TF_DataType[] dtypes,
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TF_DataType[] input_types = null, string name = "",
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Dictionary<string, AttrValue> attrs = null, OpDef op_def = null)
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{
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if (String.IsNullOrEmpty(name))
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{

‎src/TensorFlowNET.Core/OpDefLibrary.cs‎

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using System;
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using System.Collections.Generic;
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using System.IO;
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using System.Runtime.InteropServices;
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using System.Text;
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using Tensorflow;
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using static Tensorflow.OpDef.Types;
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namespace TensorFlowNET.Core
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{
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public class OpDefLibrary
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{
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public Dictionary<string, OpDef> _ops = new Dictionary<string, OpDef>();
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public void add_op_list(OpList op_list)
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{
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foreach(var op_def in op_list.Op)
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{
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add_op(op_def);
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}
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}
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public void add_op(OpDef op_def)
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{
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_ops[op_def.Name] = op_def;
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}
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public unsafe Operation _apply_op_helper(string op_type_name, string name = "", DataType? dtype = null, TensorShape shape = null)
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{
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var op_def = _ops[op_type_name];
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var status = new Status();
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var buffer = new Buffer();
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var g = ops.get_default_graph();
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if (String.IsNullOrEmpty(name))
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{
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name = op_type_name;
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}
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foreach(var attr_def in op_def.Attr)
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{
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if (attr_def.Type != "type") continue;
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var key = attr_def.Name;
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}
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foreach(var input_arg in op_def.InputArg)
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{
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}
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var attr_protos = new Dictionary<string, AttrValue>();
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foreach (var attr_def in op_def.Attr)
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{
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var key = attr_def.Name;
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var attr_value = new AttrValue();
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switch (attr_def.Type)
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{
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case "type":
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attr_value.Type = dtype.Value;
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break;
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case "shape":
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attr_value.Shape = new TensorShapeProto();
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break;
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}
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attr_protos[key] = attr_value;
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}
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var output_types = new List<DataType>();
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foreach (var arg in op_def.OutputArg)
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{
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if (!String.IsNullOrEmpty(arg.NumberAttr))
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{
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}
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else if (!String.IsNullOrEmpty(arg.TypeAttr))
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{
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output_types.Add(attr_protos[arg.TypeAttr].Type);
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}
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}
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var op = g.create_op(op_type_name, null, output_types.ToArray(),
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name: "Placeholder_1/",
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input_types: new DataType[] { },
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attrs: null,
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op_def: null);
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return op;
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}
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}
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}

‎src/TensorFlowNET.Core/TensorFlowNET.Core.csproj‎

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<None Update="tensorflow.dll">
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<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
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</None>
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<None Update="Tensorflow\op_list_proto_bytes.bin">
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<CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
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</None>
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</ItemGroup>
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</Project>

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