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Merged
merged 7 commits into from
Mar 13, 2020
Merged

support load kaldi model in python #3976

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5a40d73
support load kaldi model in python
fanlu Mar 4, 2020
422d99e
add some component
fanlu Mar 5, 2020
c7e9f4e
split one file to multi component wrap files
fanlu Mar 5, 2020
6af774b
fix some bugs and add test mdl
fanlu Mar 6, 2020
3987407
add testmode func in batchnorm pybind
fanlu Mar 6, 2020
946c81f
change StatsSum StatsSumsq to Mean Var
fanlu Mar 6, 2020
11429f2
make const
fanlu Mar 6, 2020
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18 changes: 18 additions & 0 deletions src/nnet3/nnet-normalize-component.cc
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Expand Up @@ -641,6 +641,24 @@ void BatchNormComponent::Write(std::ostream &os, bool binary) const {
WriteToken(os, binary, "</BatchNormComponent>");
}

CuVector<BaseFloat> BatchNormComponent::Mean() {
CuVector<BaseFloat> mean(stats_sum_);
if (count_ != 0) {
mean.Scale(1.0 / count_);
}
return mean;
}

CuVector<BaseFloat> BatchNormComponent::Var() {
CuVector<BaseFloat> mean(stats_sum_), var(stats_sumsq_);
if (count_ != 0) {
mean.Scale(1.0 / count_);
var.Scale(1.0 / count_);
var.AddVecVec(-1.0, mean, mean, 1.0);
}
return var;
}

void BatchNormComponent::Scale(BaseFloat scale) {
if (scale == 0) {
count_ = 0.0;
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4 changes: 2 additions & 2 deletions src/nnet3/nnet-normalize-component.h
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Expand Up @@ -224,8 +224,8 @@ class BatchNormComponent: public Component {
const CuVector<BaseFloat> &Offset() const { return offset_; }
const CuVector<BaseFloat> &Scale() const { return scale_; }

CuVector<double> &StatsSum() { return stats_sum_; }
CuVector<double> &StatsSumsq() { return stats_sumsq_; }
CuVector<BaseFloat> Mean();
CuVector<BaseFloat> Var();
double Count() { return count_; }
BaseFloat Eps() { return epsilon_; }

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Empty file modified src/pybind/nnet3/nnet3_pybind.cc
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Empty file modified src/pybind/nnet3/nnet_chain_example_pybind_test.py
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Empty file modified src/pybind/nnet3/nnet_component_itf_pybind.cc
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Empty file modified src/pybind/nnet3/nnet_convolutional_component_pybind.cc
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Empty file modified src/pybind/nnet3/nnet_nnet_pybind.cc
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48 changes: 24 additions & 24 deletions src/pybind/nnet3/nnet_nnet_pybind_test.py
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Expand Up @@ -83,10 +83,10 @@ def test_nnet_nnet(self):
elif comp_name == 'tdnn1.batchnorm':
self.assertEqual(comp_type, 'BatchNormComponent')
component.SetTestMode(True)
offset = from_dlpack(component.Offset().to_dlpack())
scale = from_dlpack(component.Scale().to_dlpack())
self.assertEqual(offset.shape, (16,))
self.assertEqual(scale.shape, (16,))
mean = from_dlpack(component.Mean().to_dlpack())
var = from_dlpack(component.Var().to_dlpack())
self.assertEqual(mean.shape, (16,))
self.assertEqual(var.shape, (16,))
elif comp_name == 'tdnnf2.linear':
self.assertEqual(comp_type, 'TdnnComponent')
linear_params = from_dlpack(
Expand All @@ -102,10 +102,10 @@ def test_nnet_nnet(self):
elif comp_name == 'tdnnf2.batchnorm':
self.assertEqual(comp_type, 'BatchNormComponent')
component.SetTestMode(True)
offset = from_dlpack(component.Offset().to_dlpack())
scale = from_dlpack(component.Scale().to_dlpack())
self.assertEqual(offset.shape, (16,))
self.assertEqual(scale.shape, (16,))
mean = from_dlpack(component.Mean().to_dlpack())
var = from_dlpack(component.Var().to_dlpack())
self.assertEqual(mean.shape, (16,))
self.assertEqual(var.shape, (16,))
elif comp_name == 'prefinal-l':
self.assertEqual(comp_type, 'LinearComponent')
params = from_dlpack(component.Params().to_dlpack())
Expand All @@ -120,21 +120,21 @@ def test_nnet_nnet(self):
elif comp_name == 'prefinal-chain.batchnorm1':
self.assertEqual(comp_type, 'BatchNormComponent')
component.SetTestMode(True)
offset = from_dlpack(component.Offset().to_dlpack())
scale = from_dlpack(component.Scale().to_dlpack())
self.assertEqual(offset.shape, (16,))
self.assertEqual(scale.shape, (16,))
mean = from_dlpack(component.Mean().to_dlpack())
var = from_dlpack(component.Var().to_dlpack())
self.assertEqual(mean.shape, (16,))
self.assertEqual(var.shape, (16,))
elif comp_name == 'prefinal-chain.linear':
self.assertEqual(comp_type, 'LinearComponent')
params = from_dlpack(component.Params().to_dlpack())
self.assertEqual(linear_params.shape, (16, 4))
elif comp_name == 'prefinal-chain.batchnorm2':
self.assertEqual(comp_type, 'BatchNormComponent')
component.SetTestMode(True)
offset = from_dlpack(component.Offset().to_dlpack())
scale = from_dlpack(component.Scale().to_dlpack())
self.assertEqual(offset.shape, (4,))
self.assertEqual(scale.shape, (4,))
mean = from_dlpack(component.Mean().to_dlpack())
var = from_dlpack(component.Var().to_dlpack())
self.assertEqual(mean.shape, (4,))
self.assertEqual(var.shape, (4,))
elif comp_name == 'output.affine':
self.assertEqual(comp_type, 'NaturalGradientAffineComponent')
linear_params = from_dlpack(
Expand All @@ -152,21 +152,21 @@ def test_nnet_nnet(self):
elif comp_name == 'prefinal-xent.batchnorm1':
self.assertEqual(comp_type, 'BatchNormComponent')
component.SetTestMode(True)
offset = from_dlpack(component.Offset().to_dlpack())
scale = from_dlpack(component.Scale().to_dlpack())
self.assertEqual(offset.shape, (16,))
self.assertEqual(scale.shape, (16,))
mean = from_dlpack(component.Mean().to_dlpack())
var = from_dlpack(component.Var().to_dlpack())
self.assertEqual(mean.shape, (16,))
self.assertEqual(var.shape, (16,))
elif comp_name == 'prefinal-xent.linear':
self.assertEqual(comp_type, 'LinearComponent')
params = from_dlpack(component.Params().to_dlpack())
self.assertEqual(linear_params.shape, (16, 4))
elif comp_name == 'prefinal-xent.batchnorm2':
self.assertEqual(comp_type, 'BatchNormComponent')
component.SetTestMode(True)
offset = from_dlpack(component.Offset().to_dlpack())
scale = from_dlpack(component.Scale().to_dlpack())
self.assertEqual(offset.shape, (4,))
self.assertEqual(scale.shape, (4,))
mean = from_dlpack(component.Mean().to_dlpack())
var = from_dlpack(component.Var().to_dlpack())
self.assertEqual(mean.shape, (4,))
self.assertEqual(var.shape, (4,))
elif comp_name == 'output-xent.affine':
self.assertEqual(comp_type, 'NaturalGradientAffineComponent')
linear_params = from_dlpack(
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6 changes: 2 additions & 4 deletions src/pybind/nnet3/nnet_normalize_component_pybind.cc
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Expand Up @@ -26,10 +26,8 @@ using namespace kaldi::nnet3;
void pybind_nnet_normalize_component(py::module& m) {
using PyClass = kaldi::nnet3::BatchNormComponent;
py::class_<PyClass, Component>(m, "BatchNormComponent")
.def("StatsSum", &PyClass::StatsSum, py::return_value_policy::reference)
.def("StatsSumsq", &PyClass::StatsSumsq,
py::return_value_policy::reference)
.def("Mean", &PyClass::Mean, py::return_value_policy::reference)
.def("Mean", &PyClass::Mean)
.def("Var", &PyClass::Var)
.def("Count", &PyClass::Count)
.def("Eps", &PyClass::Eps)
.def("SetTestMode", &PyClass::SetTestMode, py::arg("test_mode"))
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Empty file modified src/pybind/nnet3/nnet_normalize_component_pybind.h
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Empty file modified src/pybind/nnet3/nnet_simple_component_pybind.cc
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