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CApiColocationTest.cs 3.6 kB

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  1. using Microsoft.VisualStudio.TestTools.UnitTesting;
  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_api_test.cc
  11. /// `class CApiColocationTest`
  12. /// </summary>
  13. [TestClass]
  14. public class CApiColocationTest : CApiTest, IDisposable
  15. {
  16. private Graph graph_ = new Graph();
  17. private Status s_ = new Status();
  18. private Operation feed1_;
  19. private Operation feed2_;
  20. private Operation constant_;
  21. private OperationDescription desc_;
  22. [TestInitialize]
  23. public void SetUp()
  24. {
  25. feed1_ = c_test_util.Placeholder(graph_, s_, "feed1");
  26. feed2_ = c_test_util.Placeholder(graph_, s_, "feed2");
  27. constant_ = c_test_util.ScalarConst(10, graph_, s_);
  28. desc_ = graph_.NewOperation("AddN", "add");
  29. TF_Output[] inputs = { new TF_Output(feed1_, 0), new TF_Output(constant_, 0) };
  30. desc_.AddInputList(inputs);
  31. }
  32. private void SetViaStringList(OperationDescription desc, string[] list)
  33. {
  34. string[] list_ptrs = new string[list.Length];
  35. uint[] list_lens = new uint[list.Length];
  36. StringVectorToArrays(list, list_ptrs, list_lens);
  37. c_api.TF_SetAttrStringList(desc, "_class", list_ptrs, list_lens, list.Length);
  38. }
  39. private void StringVectorToArrays(string[] v, string[] ptrs, uint[] lens)
  40. {
  41. for (int i = 0; i < v.Length; ++i)
  42. {
  43. ptrs[i] = v[i];// Marshal.StringToHGlobalAnsi(v[i]);
  44. lens[i] = (uint)v[i].Length;
  45. }
  46. }
  47. private void FinishAndVerify(OperationDescription desc, string[] expected)
  48. {
  49. Operation op = c_api.TF_FinishOperation(desc_, s_);
  50. ASSERT_EQ(TF_Code.TF_OK, s_.Code);
  51. VerifyCollocation(op, expected);
  52. }
  53. private void VerifyCollocation(Operation op, string[] expected)
  54. {
  55. var handle = c_api.TF_OperationGetAttrMetadata(op, "_class", s_);
  56. TF_AttrMetadata m = new TF_AttrMetadata();
  57. if (expected.Length == 0)
  58. {
  59. ASSERT_EQ(TF_Code.TF_INVALID_ARGUMENT, s_.Code);
  60. EXPECT_EQ("Operation 'add' has no attr named '_class'.", s_.Message);
  61. return;
  62. }
  63. EXPECT_EQ(TF_Code.TF_OK, s_.Code);
  64. EXPECT_EQ(1, m.is_list);
  65. EXPECT_EQ(expected.Length, m.list_size);
  66. EXPECT_EQ(TF_AttrType.TF_ATTR_STRING, m.type);
  67. string[] values = new string[expected.Length];
  68. uint[] lens = new uint[expected.Length];
  69. string[] storage = new string[m.total_size];
  70. //c_api.TF_OperationGetAttrStringList(op, "_class", values, lens, expected.Length, storage, m.total_size, s_);
  71. EXPECT_EQ(TF_Code.TF_OK, s_.Code);
  72. for (int i = 0; i < expected.Length; ++i)
  73. {
  74. EXPECT_EQ(expected[i], values[i] + lens[i]);
  75. }
  76. }
  77. [TestMethod]
  78. public void ColocateWith()
  79. {
  80. }
  81. [TestMethod]
  82. public void StringList()
  83. {
  84. SetViaStringList(desc_, new string[] { "loc:@feed1" });
  85. FinishAndVerify(desc_, new string[] { "loc:@feed1" });
  86. }
  87. [TestCleanup]
  88. public void Dispose()
  89. {
  90. graph_.Dispose();
  91. s_.Dispose();
  92. }
  93. }
  94. }

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。

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