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Fix calculations in gru_unit_op to be consistent with gru_op

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release/0.11.0
guosheng 7 years ago
parent f191c82010
commit b6b7ab63c6
2 changed files with 46 additions and 39 deletions
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70
paddle/operators/gru_unit_op.h
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@ -146,35 +146,27 @@ class GRUUnitGradKernel : public framework::OpKernel<T> {
auto* weight_grad =
context.Output<Tensor>(framework::GradVarName("Weight"));
auto* bias_grad = context.Output<Tensor>(framework::GradVarName("Bias"));
input_grad->mutable_data<T>(context.GetPlace());
hidden_prev_grad->mutable_data<T>(context.GetPlace());
weight_grad->mutable_data<T>(context.GetPlace());
Tensor gate_grad;
gate_grad.mutable_data<T>(input->dims(), context.GetPlace());
Tensor reset_hidden_prev_grad;
reset_hidden_prev_grad.mutable_data<T>(reset_hidden_prev->dims(),
context.GetPlace());
int batch_size = input->dims()[0];
int frame_size = hidden_prev->dims()[1];
const T* hidden_prev_data = hidden_prev->data<T>();
T* hidden_prev_grad_data = hidden_prev_grad->data<T>();
const T* weight_data = weight->data<T>();
T* weight_grad_data = weight_grad->data<T>();
T* gate_grad_data = gate_grad.data<T>();
T* gate_grad_data =
gate_grad.mutable_data<T>(input->dims(), context.GetPlace());
const T* reset_hidden_prev_data = reset_hidden_prev->data<T>();
T* reset_hidden_prev_grad_data = reset_hidden_prev_grad.data<T>();
T* reset_hidden_prev_grad_data = reset_hidden_prev_grad.mutable_data<T>(
reset_hidden_prev->dims(), context.GetPlace());
auto h_p = EigenMatrix<T>::From(*hidden_prev);
auto g = EigenMatrix<T>::From(*gate);
auto d_h = EigenMatrix<T>::From(*hidden_grad);
auto d_x = EigenMatrix<T>::From(*input_grad);
auto d_h_p = EigenMatrix<T>::From(*hidden_prev_grad);
auto d_g = EigenMatrix<T>::From(gate_grad);
auto d_r_h_p = EigenMatrix<T>::From(reset_hidden_prev_grad);
auto place = context.GetEigenDevice<Place>();
int batch_size = input->dims()[0];
int frame_size = hidden_prev->dims()[1];
Eigen::array<int, 2> extents({{batch_size, frame_size}});
Eigen::array<int, 2> u_offsets({{0, 0}});
auto u = g.slice(u_offsets, extents); // update gate
@ -195,28 +187,42 @@ class GRUUnitGradKernel : public framework::OpKernel<T> {
gate_grad_data + frame_size * 2, frame_size * 3,
weight_data + frame_size * frame_size * 2, frame_size,
0, reset_hidden_prev_grad_data, frame_size);
// backward for state_weight
math::gemm<Place, T>(
context.device_context(), true, false, frame_size, frame_size,
batch_size, 1, reset_hidden_prev_data, frame_size,
gate_grad_data + frame_size * 2, frame_size * 3, 0,
weight_grad_data + frame_size * frame_size * 2, frame_size);
// backward for unactivated reset gate
ActGradCompute(context.Attr<int>("gate_activation"), place, r, r,
d_g.slice(r_offsets, extents), d_r_h_p * h_p);
// backward for update_gate_weight and reset_gate_weight
math::gemm<Place, T>(context.device_context(), true, false, frame_size,
frame_size * 2, batch_size, 1, hidden_prev_data,
frame_size, gate_grad_data, frame_size * 3, 0,
weight_grad_data, frame_size * 2);
// backward for weight
if (weight_grad) {
T* weight_grad_data = weight_grad->mutable_data<T>(context.GetPlace());
// backward for state_weight
math::gemm<Place, T>(
context.device_context(), true, false, frame_size, frame_size,
batch_size, 1, reset_hidden_prev_data, frame_size,
gate_grad_data + frame_size * 2, frame_size * 3, 0,
weight_grad_data + frame_size * frame_size * 2, frame_size);
// backward for update_gate_weight and reset_gate_weight
math::gemm<Place, T>(context.device_context(), true, false, frame_size,
frame_size * 2, batch_size, 1, hidden_prev_data,
frame_size, gate_grad_data, frame_size * 3, 0,
weight_grad_data, frame_size * 2);
}
// backward for hidden_prev
d_h_p.device(place) = d_r_h_p * r + d_h * (u.constant(T(1)) - u);
math::gemm<Place, T>(context.device_context(), false, true, batch_size,
frame_size, frame_size * 2, 1, gate_grad_data,
frame_size * 3, weight_data, frame_size * 2, 1,
hidden_prev_grad_data, frame_size);
if (hidden_prev_grad) {
T* hidden_prev_grad_data =
hidden_prev_grad->mutable_data<T>(context.GetPlace());
auto d_h_p = EigenMatrix<T>::From(*hidden_prev_grad);
d_h_p.device(place) = d_r_h_p * r + d_h * (u.constant(T(1)) - u);
math::gemm<Place, T>(context.device_context(), false, true, batch_size,
frame_size, frame_size * 2, 1, gate_grad_data,
frame_size * 3, weight_data, frame_size * 2, 1,
hidden_prev_grad_data, frame_size);
}
// backward for input
d_x.device(place) = d_g;
if (input_grad) {
input_grad->mutable_data<T>(context.GetPlace());
auto d_x = EigenMatrix<T>::From(*input_grad);
d_x.device(place) = d_g;
}
// backward for bias
if (bias_grad) {
bias_grad->mutable_data<T>(context.GetPlace());

15
python/paddle/v2/fluid/tests/test_gru_unit_op.py
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@ -28,8 +28,8 @@ def relu(x):
class TestGRUUnitOp(OpTest):
batch_size = 3
frame_size = 5
batch_size = 5
frame_size = 10
activate = {
GRUActivationType.identity: identity,
GRUActivationType.sigmoid: sigmoid,
@ -92,9 +92,7 @@ class TestGRUUnitOp(OpTest):
self.check_output()
def test_check_grad(self):
self.check_grad(
['Input', 'HiddenPrev', 'Weight'], ['Hidden'],
max_relative_error=0.007)
self.check_grad(['Input', 'HiddenPrev', 'Weight'], ['Hidden'])
class TestGRUUnitOpWithBias(TestGRUUnitOp):
@ -110,9 +108,12 @@ class TestGRUUnitOpWithBias(TestGRUUnitOp):
}
def test_check_grad(self):
self.check_grad(['Input', 'HiddenPrev', 'Weight', 'Bias'], ['Hidden'])
def test_check_grad_ingore_input(self):
self.check_grad(
['Input', 'HiddenPrev', 'Weight', 'Bias'], ['Hidden'],
max_relative_error=0.007)
['HiddenPrev', 'Weight', 'Bias'], ['Hidden'],
no_grad_set=set('Input'))
if __name__ == '__main__':

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