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jit.go
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jit.go
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package nn
import (
"io"
"log"
"strings"
"github.com/nullbull/gotch/ts"
)
// TrainableCModule is a trainable version of JIT Pytorch module
//
// These modules can be created via TorchScript python API.
// See: https://pytorch.org/docs/stable/jit.html
type TrainableCModule struct {
Inner *ts.CModule
}
// TrainableCModuleLoad loads a PyTorch saved JIT module from a file and adds
// tensors (weights) to `varstore` so that module can be trained.
func TrainableCModuleLoad(p *Path, file string) (*TrainableCModule, error) {
inner, err := ts.ModuleLoadOnDevice(file, p.Device())
if err != nil {
return nil, err
}
namedTensors, err := inner.NamedParameters()
if err != nil {
return nil, err
}
// Add named tensors (weights) to varstore
for _, namedTensor := range namedTensors {
name := strings.ReplaceAll(namedTensor.Name, ".", "_")
requiresGrad := namedTensor.Tensor.MustRequiresGrad()
// NOTE: return is a newly created and added tensor in varstore.
// This tensor is different from input named tensor.
// If not using, just ignore it. Drop it, will drop tensor at varstore.
_ = p.MustAdd(name, namedTensor.Tensor, requiresGrad)
// Clean-up named tensors.
namedTensor.Tensor.MustDrop()
}
return &TrainableCModule{inner}, nil
}
func TrainableCModuleLoadData(p *Path, stream io.Reader) (*TrainableCModule, error) {
inner, err := ts.ModuleLoadDataOnDevice(stream, p.Device())
if err != nil {
return nil, err
}
namedTensors, err := inner.NamedParameters()
if err != nil {
return nil, err
}
// Add named tensors (weights) to varstore
for _, namedTensor := range namedTensors {
name := strings.ReplaceAll(namedTensor.Name, ".", "_")
requiresGrad := namedTensor.Tensor.MustRequiresGrad()
// NOTE: return is a newly created and added tensor in varstore.
// This tensor is different from input named tensor.
// If not using, just ignore it. Drop it, will drop tensor at varstore.
_ = p.MustAdd(name, namedTensor.Tensor, requiresGrad)
// Clean-up named tensors.
namedTensor.Tensor.MustDrop()
}
return &TrainableCModule{inner}, nil
}
// Save saves TrainableCModule to specified file.
func (m *TrainableCModule) Save(file string) error {
return m.Inner.Save(file)
}
// ForwardT implements ModuleT for TrainableCModule.
// NOTE: train parameter will not be used.
func (m *TrainableCModule) ForwardT(x *ts.Tensor, train bool) *ts.Tensor {
retVal, err := m.Inner.ForwardTs([]*ts.Tensor{x})
if err != nil {
log.Fatal(err)
}
return retVal
}
// SetTrain set TrainableCModule to train mode
func (m *TrainableCModule) SetTrain() {
m.Inner.SetTrain()
}
// SetEval set TrainableCModule to inference mode
func (m *TrainableCModule) SetEval() {
m.Inner.SetEval()
}