(t *testing.T)
| 24 | ) |
| 25 | |
| 26 | func TestAddGradients(t *testing.T) { |
| 27 | var ( |
| 28 | s = NewScope() |
| 29 | x1 = Placeholder(s.SubScope("x1"), tf.Float) |
| 30 | x2 = Placeholder(s.SubScope("x2"), tf.Float) |
| 31 | y0 = Square(s.SubScope("y0"), x1) |
| 32 | y1 = Square(s.SubScope("y1"), y0) |
| 33 | y2 = AddN(s.SubScope("y2"), []tf.Output{y0, x2}) |
| 34 | ) |
| 35 | |
| 36 | grads0 := Gradients(s, []tf.Output{y1}, []tf.Output{x1}) |
| 37 | if err := s.Err(); err != nil { |
| 38 | t.Fatal(err) |
| 39 | } |
| 40 | if len(grads0) != 1 { |
| 41 | t.Fatal(len(grads0)) |
| 42 | } |
| 43 | if grads0[0].DataType() != tf.Float { |
| 44 | t.Fatalf("Got DataType %v, wanted %v", grads0[0].DataType(), tf.Float) |
| 45 | } |
| 46 | |
| 47 | sub := s.SubScope("sub") |
| 48 | grads1 := Gradients(sub, []tf.Output{y2}, []tf.Output{x1, x2}) |
| 49 | if err := sub.Err(); err != nil { |
| 50 | t.Fatal(err) |
| 51 | } |
| 52 | if len(grads1) != 2 { |
| 53 | t.Fatal(len(grads1)) |
| 54 | } |
| 55 | if grads1[0].DataType() != tf.Float { |
| 56 | t.Fatalf("Got DataType %v, wanted %v", grads1[0].DataType(), tf.Float) |
| 57 | } |
| 58 | if grads1[1].DataType() != tf.Float { |
| 59 | t.Fatalf("Got DataType %v, wanted %v", grads1[1].DataType(), tf.Float) |
| 60 | } |
| 61 | |
| 62 | graph, err := sub.Finalize() |
| 63 | if err != nil { |
| 64 | t.Fatal(err) |
| 65 | } |
| 66 | sess, err := tf.NewSession(graph, nil) |
| 67 | if err != nil { |
| 68 | t.Fatal(err) |
| 69 | } |
| 70 | |
| 71 | c1, _ := tf.NewTensor(float32(3.0)) |
| 72 | c2, _ := tf.NewTensor(float32(3.0)) |
| 73 | outputs, err := sess.Run( |
| 74 | map[tf.Output]*tf.Tensor{x1: c1, x2: c2}, |
| 75 | []tf.Output{grads0[0], grads1[0], grads1[1]}, |
| 76 | nil) |
| 77 | if err != nil { |
| 78 | t.Fatal(err) |
| 79 | } |
| 80 | if len(outputs) != 3 { |
| 81 | t.Fatal(len(outputs)) |
| 82 | } |
| 83 | if outputs[0].Value().(float32) != 108.0 { |
nothing calls this directly
no test coverage detected