feat(tensor/index_test.go): added
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sugarme
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@ -5,6 +5,7 @@
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- [Quick start guide](how-quickstart.md)
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- [Installation](how-installation.md)
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- [Cloud training](how-cloud.md)
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- [Use pre-trained model](how-pretrained.md)
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## General
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@ -26,6 +27,7 @@
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- [Linear](nn-linear.md)
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- [Convolutional Neural Network](nn-cnn.md)
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- [Recurrent Neural Network](nn-rnn.md)
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- [JIT](nn-jit.md)
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## Vision
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@ -254,7 +254,6 @@ func (ts Tensor) indexer(indexSpec []TensorIndexer) (retVal Tensor, err error) {
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switch reflect.TypeOf(spec).Name() {
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case "InsertNewAxis":
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fmt.Println(currIdx)
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nextTensor, err = currTensor.Unsqueeze(currIdx, true)
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if err != nil {
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return retVal, err
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@ -8,19 +8,76 @@ import (
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ts "github.com/sugarme/gotch/tensor"
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)
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func TestNewInsertAxis(t *testing.T) {
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func TestIntegerIndex(t *testing.T) {
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// [ 0 1 2
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// 3 4 5 ]
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tensor := ts.MustArange1(ts.IntScalar(0), ts.IntScalar(2*3), gotch.Int64, gotch.CPU).MustView([]int64{2, 3}, true)
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// tensor, err := ts.NewTensorFromData([]bool{true, false, false, false, false, false}, []int64{2, 3})
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// if err != nil {
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// panic(err)
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// }
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idx1 := []ts.TensorIndexer{
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ts.NewSelect(1),
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}
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result1 := tensor.Idx(idx1)
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want1 := []int64{3, 4, 5}
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want1Shape := []int64{3}
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got1 := result1.Vals()
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got1Shape := result1.MustSize()
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if !reflect.DeepEqual(want1, got1) {
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t.Errorf("Expected tensor values: %v\n", want1)
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t.Errorf("Got tensor values: %v\n", got1)
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}
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if !reflect.DeepEqual(want1Shape, got1Shape) {
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t.Errorf("Expected tensor values: %v\n", want1Shape)
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t.Errorf("Got tensor values: %v\n", got1Shape)
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}
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idx2 := []ts.TensorIndexer{
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ts.NewNarrow(0, tensor.MustSize()[0]),
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ts.NewSelect(2),
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}
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result2 := tensor.Idx(idx2)
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want2 := []int64{2, 5}
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want2Shape := []int64{2}
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got2 := result2.Vals()
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got2Shape := result2.MustSize()
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if !reflect.DeepEqual(want2, got2) {
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t.Errorf("Expected tensor values: %v\n", want2)
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t.Errorf("Got tensor values: %v\n", got2)
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}
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if !reflect.DeepEqual(want2Shape, got2Shape) {
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t.Errorf("Expected tensor values: %v\n", want2Shape)
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t.Errorf("Got tensor values: %v\n", got2Shape)
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}
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idx3 := []ts.TensorIndexer{
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ts.NewNarrow(0, tensor.MustSize()[0]),
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ts.NewSelect(-2),
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}
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result3 := tensor.Idx(idx3)
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want3 := []int64{1, 4}
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want3Shape := []int64{2}
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got3 := result3.Vals()
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got3Shape := result3.MustSize()
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if !reflect.DeepEqual(want3, got3) {
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t.Errorf("Expected tensor values: %v\n", want3)
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t.Errorf("Got tensor values: %v\n", got3)
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}
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if !reflect.DeepEqual(want3Shape, got3Shape) {
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t.Errorf("Expected tensor values: %v\n", want3Shape)
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t.Errorf("Got tensor values: %v\n", got3Shape)
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}
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}
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func TestNewInsertAxis(t *testing.T) {
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tensor := ts.MustArange1(ts.IntScalar(0), ts.IntScalar(2*3), gotch.Int64, gotch.CPU).MustView([]int64{2, 3}, true)
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var idxs1 []ts.TensorIndexer = []ts.TensorIndexer{
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ts.NewInsertNewAxis(),
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}
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result1 := tensor.Idx(idxs1)
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want1 := []int64{1, 2, 3}
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got1 := result1.MustSize()
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if !reflect.DeepEqual(want1, got1) {
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t.Errorf("Expected a tensor shape: %v\n", want1)
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t.Errorf("Got a tensor shape: %v\n", got1)
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@ -30,12 +87,9 @@ func TestNewInsertAxis(t *testing.T) {
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ts.NewNarrow(0, tensor.MustSize()[0]),
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ts.NewInsertNewAxis(),
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}
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result2 := tensor.Idx(idxs2)
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want2 := []int64{2, 1, 3}
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got2 := result2.MustSize()
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if !reflect.DeepEqual(want2, got2) {
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t.Errorf("Expected a tensor shape: %v\n", want2)
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t.Errorf("Got a tensor shape: %v\n", got2)
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@ -46,14 +100,94 @@ func TestNewInsertAxis(t *testing.T) {
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ts.NewNarrow(0, tensor.MustSize()[1]),
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ts.NewInsertNewAxis(),
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}
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result3 := tensor.Idx(idxs3)
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want3 := []int64{2, 3, 1}
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got3 := result3.MustSize()
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if !reflect.DeepEqual(want3, got3) {
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t.Errorf("Expected a tensor shape: %v\n", want3)
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t.Errorf("Got a tensor shape: %v\n", got3)
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}
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}
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func TestRangeIndex(t *testing.T) {
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// Range
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tensor1 := ts.MustArange1(ts.IntScalar(0), ts.IntScalar(4*3), gotch.Int64, gotch.CPU).MustView([]int64{4, 3}, true)
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idx1 := []ts.TensorIndexer{
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ts.NewNarrow(1, 3),
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}
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result1 := tensor1.Idx(idx1)
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want1 := []int64{3, 4, 5, 6, 7, 8}
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want1Shape := []int64{2, 3}
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got1 := result1.Vals()
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got1Shape := result1.MustSize()
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if !reflect.DeepEqual(want1, got1) {
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t.Errorf("Expected tensor values: %v\n", want1)
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t.Errorf("Got tensor values: %v\n", got1)
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}
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if !reflect.DeepEqual(want1Shape, got1Shape) {
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t.Errorf("Expected tensor values: %v\n", want1Shape)
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t.Errorf("Got tensor values: %v\n", got1Shape)
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}
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// Full range
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tensor2 := ts.MustArange1(ts.IntScalar(0), ts.IntScalar(2*3), gotch.Int64, gotch.CPU).MustView([]int64{2, 3}, true)
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idx2 := []ts.TensorIndexer{
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ts.NewNarrow(0, tensor2.MustSize()[0]),
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}
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result2 := tensor2.Idx(idx2)
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want2 := []int64{0, 1, 2, 3, 4, 5}
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want2Shape := []int64{2, 3}
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got2 := result2.Vals()
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got2Shape := result2.MustSize()
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if !reflect.DeepEqual(want2, got2) {
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t.Errorf("Expected tensor values: %v\n", want2)
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t.Errorf("Got tensor values: %v\n", got2)
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}
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if !reflect.DeepEqual(want2Shape, got2Shape) {
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t.Errorf("Expected tensor values: %v\n", want2Shape)
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t.Errorf("Got tensor values: %v\n", got2Shape)
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}
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// Range from
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tensor3 := ts.MustArange1(ts.IntScalar(0), ts.IntScalar(4*3), gotch.Int64, gotch.CPU).MustView([]int64{4, 3}, true)
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idx3 := []ts.TensorIndexer{
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ts.NewNarrow(2, tensor3.MustSize()[0]),
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}
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result3 := tensor3.Idx(idx3)
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want3 := []int64{6, 7, 8, 9, 10, 11}
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want3Shape := []int64{2, 3}
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got3 := result3.Vals()
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got3Shape := result3.MustSize()
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if !reflect.DeepEqual(want3, got3) {
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t.Errorf("Expected tensor values: %v\n", want3)
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t.Errorf("Got tensor values: %v\n", got3)
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}
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if !reflect.DeepEqual(want3Shape, got3Shape) {
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t.Errorf("Expected tensor values: %v\n", want3Shape)
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t.Errorf("Got tensor values: %v\n", got3Shape)
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}
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// Range to
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tensor4 := ts.MustArange1(ts.IntScalar(0), ts.IntScalar(4*3), gotch.Int64, gotch.CPU).MustView([]int64{4, 3}, true)
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idx4 := []ts.TensorIndexer{
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ts.NewNarrow(0, 2),
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}
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result4 := tensor4.Idx(idx4)
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want4 := []int64{0, 1, 2, 3, 4, 5}
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want4Shape := []int64{2, 3}
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got4 := result4.Vals()
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got4Shape := result4.MustSize()
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if !reflect.DeepEqual(want4, got4) {
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t.Errorf("Expected tensor values: %v\n", want4)
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t.Errorf("Got tensor values: %v\n", got4)
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}
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if !reflect.DeepEqual(want4Shape, got4Shape) {
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t.Errorf("Expected tensor values: %v\n", want4Shape)
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t.Errorf("Got tensor values: %v\n", got4Shape)
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}
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}
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func TestSliceIndex(t *testing.T) {
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// TODO
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}
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@ -1029,6 +1029,38 @@ func (ts Tensor) Values() []float64 {
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return values
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}
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// Vals returns tensor values in a slice
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// NOTE: need a type insersion to get runtime type
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// E.g. res := xs.Vals().([]int64)
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func (ts Tensor) Vals() (retVal interface{}) {
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dtype := ts.DType()
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numel := ts.Numel()
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switch dtype.Name() {
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case "uint8":
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retVal = make([]uint8, numel)
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case "int8":
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retVal = make([]int8, numel)
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case "int16":
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retVal = make([]int16, numel)
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case "int32":
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retVal = make([]int32, numel)
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case "int64":
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retVal = make([]int64, numel)
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case "float32":
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retVal = make([]float32, numel)
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case "float64":
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retVal = make([]float64, numel)
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case "bool":
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retVal = make([]bool, numel)
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default:
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log.Fatalf("Unsupported dtype (%v)", dtype)
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}
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ts.CopyData(retVal, numel)
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return retVal
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}
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// FlatView flattens a tensor.
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//
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// This returns a flattened version of the given tensor. The first dimension
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