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CSession.cs 3.2 kB

6 years ago
6 years ago
6 years ago
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  1. using NumSharp.Core;
  2. using System;
  3. using System.Collections.Generic;
  4. using System.Runtime.InteropServices;
  5. using System.Text;
  6. using Tensorflow;
  7. namespace TensorFlowNET.UnitTest
  8. {
  9. /// <summary>
  10. /// tensorflow\c\c_test_util.cc
  11. /// </summary>
  12. public class CSession
  13. {
  14. private IntPtr session_;
  15. private List<IntPtr> inputs_ = new List<IntPtr>();
  16. private List<IntPtr> input_values_ = new List<IntPtr>();
  17. private List<IntPtr> outputs_ = new List<IntPtr>();
  18. private List<IntPtr> output_values_ = new List<IntPtr>();
  19. private List<IntPtr> targets_ = new List<IntPtr>();
  20. public CSession(Graph graph, Status s, bool user_XLA = false)
  21. {
  22. var opts = new SessionOptions();
  23. session_ = new Session(graph, opts, s);
  24. }
  25. public void SetInputs(Dictionary<IntPtr, IntPtr> inputs)
  26. {
  27. DeleteInputValues();
  28. inputs_.Clear();
  29. foreach (var input in inputs)
  30. {
  31. var handle = Marshal.AllocHGlobal(Marshal.SizeOf<TF_Output>());
  32. Marshal.StructureToPtr(new TF_Output(input.Key, 0), handle, false);
  33. inputs_.Add(handle);
  34. input_values_.Add(input.Value);
  35. }
  36. }
  37. private void DeleteInputValues()
  38. {
  39. for (var i = 0; i < input_values_.Count; ++i)
  40. {
  41. //input_values_[i].Dispose();
  42. }
  43. input_values_.Clear();
  44. }
  45. public void SetOutputs(List<IntPtr> outputs)
  46. {
  47. ResetOutputValues();
  48. outputs_.Clear();
  49. foreach (var output in outputs)
  50. {
  51. var handle = Marshal.AllocHGlobal(Marshal.SizeOf<TF_Output>());
  52. Marshal.StructureToPtr(new TF_Output(output, 0), handle, true);
  53. outputs_.Add(handle);
  54. handle = Marshal.AllocHGlobal(Marshal.SizeOf<IntPtr>());
  55. output_values_.Add(IntPtr.Zero);
  56. }
  57. }
  58. private void ResetOutputValues()
  59. {
  60. for (var i = 0; i < output_values_.Count; ++i)
  61. {
  62. //if (output_values_[i] != IntPtr.Zero)
  63. //output_values_[i].Dispose();
  64. }
  65. output_values_.Clear();
  66. }
  67. public unsafe void Run(Status s)
  68. {
  69. IntPtr inputs_ptr = inputs_.Count == 0 ? IntPtr.Zero : inputs_[0];
  70. IntPtr input_values_ptr = inputs_.Count == 0 ? IntPtr.Zero : input_values_[0];
  71. IntPtr outputs_ptr = outputs_.Count == 0 ? IntPtr.Zero : outputs_[0];
  72. IntPtr[] output_values_ptr = output_values_.ToArray();// output_values_.Count == 0 ? IntPtr.Zero : output_values_[0];
  73. IntPtr targets_ptr = IntPtr.Zero;
  74. c_api.TF_SessionRun(session_, null, inputs_ptr, input_values_ptr, 0,
  75. outputs_ptr, output_values_ptr, outputs_.Count,
  76. targets_ptr, targets_.Count,
  77. IntPtr.Zero, s);
  78. s.Check();
  79. output_values_[0] = output_values_ptr[0];
  80. }
  81. public IntPtr output_tensor(int i)
  82. {
  83. return output_values_[i];
  84. }
  85. }
  86. }

tensorflow框架的.NET版本,提供了丰富的特性和API,可以借此很方便地在.NET平台下搭建深度学习训练与推理流程。

Contributors (1)