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提交 9b16e540 编写于 作者: Q Qiao Longfei
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update gru_grad_op 

test=develop
上级 e477d789
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Showing with 55 addition and 34 deletion
paddle/fluid/operators/math/detail/gru_cpu_kernel.h
浏览文件 @ 9b16e540
......@@ -256,7 +256,8 @@ void hl_naive_gru_backward_state_grad(OpStateGrad op_state_grad, T *gate_value,
T *gate_grad, T *prev_out_value,
T *prev_out_grad, T *output_grad,
int frame_size,
ActivationType active_node) {
ActivationType active_node,
bool origin_mode) {
T r_update_gate_value;
T r_update_gate_grad;
T r_frame_state_value;
......@@ -282,7 +283,7 @@ void hl_naive_gru_backward_state_grad(OpStateGrad op_state_grad, T *gate_value,
op_state_grad(&r_update_gate_value, &r_update_gate_grad,
&r_frame_state_value, &r_frame_state_grad, &r_prev_out_value,
&r_prev_out_grad, &r_out_grad, active_node);
&r_prev_out_grad, &r_out_grad, active_node, origin_mode);
update_gate_grad[i] = r_update_gate_grad;
frame_state_grad[i] = r_frame_state_grad;
......@@ -297,7 +298,8 @@ void hl_naive_gru_backward_reset_grad(OpResetGrad op_reset_grad, T *gate_value,
T *gate_grad, T *prev_out_value,
T *prev_out_grad, T *reset_output_grad,
int frame_size,
ActivationType active_gate) {
ActivationType active_gate,
bool origin_mode) {
T r_update_gate_value;
T r_update_gate_grad;
T r_reset_gate_value;
......@@ -327,7 +329,8 @@ void hl_naive_gru_backward_reset_grad(OpResetGrad op_reset_grad, T *gate_value,
op_reset_grad(&r_update_gate_value, &r_update_gate_grad,
&r_reset_gate_value, &r_reset_gate_grad, &r_prev_out_value,
&r_prev_out_grad, &r_reset_output_grad, active_gate);
&r_prev_out_grad, &r_reset_output_grad, active_gate,
origin_mode);
update_gate_grad[i] = r_update_gate_grad;
reset_gate_grad[i] = r_reset_gate_grad;
......@@ -341,8 +344,8 @@ template <class OpStateGrad, typename T>
void hl_avx_gru_backward_state_grad(OpStateGrad op_state_grad, T *gate_value,
T *gate_grad, T *prev_out_value,
T *prev_out_grad, T *output_grad,
int frame_size,
ActivationType active_node) {
int frame_size, ActivationType active_node,
bool origin_mode) {
#ifdef __AVX__
__m256 r_update_gate_value;
__m256 r_update_gate_grad;
......@@ -371,7 +374,7 @@ void hl_avx_gru_backward_state_grad(OpStateGrad op_state_grad, T *gate_value,
op_state_grad(&r_update_gate_value, &r_update_gate_grad,
&r_frame_state_value, &r_frame_state_grad, &r_prev_out_value,
&r_prev_out_grad, &r_out_grad, active_node);
&r_prev_out_grad, &r_out_grad, active_node, origin_mode);
update_gate_grad[i] = r_update_gate_grad;
frame_state_grad[i] = r_frame_state_grad;
......@@ -386,8 +389,8 @@ template <class OpResetGrad, typename T>
void hl_avx_gru_backward_reset_grad(OpResetGrad op_reset_grad, T *gate_value,
T *gate_grad, T *prev_out_value,
T *prev_out_grad, T *reset_output_grad,
int frame_size,
ActivationType active_gate) {
int frame_size, ActivationType active_gate,
bool origin_mode) {
#ifdef __AVX__
__m256 r_update_gate_value;
__m256 r_update_gate_grad;
......@@ -419,7 +422,8 @@ void hl_avx_gru_backward_reset_grad(OpResetGrad op_reset_grad, T *gate_value,
op_reset_grad(&r_update_gate_value, &r_update_gate_grad,
&r_reset_gate_value, &r_reset_gate_grad, &r_prev_out_value,
&r_prev_out_grad, &r_reset_output_grad, active_gate);
&r_prev_out_grad, &r_reset_output_grad, active_gate,
origin_mode);
update_gate_grad[i] = r_update_gate_grad;
reset_gate_grad[i] = r_reset_gate_grad;
......@@ -434,16 +438,18 @@ template <class OpStateGrad, typename T>
inline void backward_state_grad(OpStateGrad op_state_grad,
GRUMetaValue<T> value, GRUMetaGrad<T> grad,
int frame_size, int batch_size,
ActivationType active_node) {
ActivationType active_node, bool origin_mode) {
for (int b = 0; b < batch_size; b++) {
if (OpStateGrad::avx && !(frame_size & (8 - 1)) && (sizeof(T) == 4)) {
hl_avx_gru_backward_state_grad(
op_state_grad, value.gate_value, grad.gate_grad, value.prev_out_value,
grad.prev_out_grad, grad.output_grad, frame_size, active_node);
hl_avx_gru_backward_state_grad(op_state_grad, value.gate_value,
grad.gate_grad, value.prev_out_value,
grad.prev_out_grad, grad.output_grad,
frame_size, active_node, origin_mode);
} else {
hl_naive_gru_backward_state_grad(
op_state_grad, value.gate_value, grad.gate_grad, value.prev_out_value,
grad.prev_out_grad, grad.output_grad, frame_size, active_node);
hl_naive_gru_backward_state_grad(op_state_grad, value.gate_value,
grad.gate_grad, value.prev_out_value,
grad.prev_out_grad, grad.output_grad,
frame_size, active_node, origin_mode);
}
value.gate_value += frame_size * 3;
......@@ -463,16 +469,18 @@ template <class OpResetGrad, typename T>
inline void backward_reset_grad(OpResetGrad op_reset_grad,
GRUMetaValue<T> value, GRUMetaGrad<T> grad,
int frame_size, int batch_size,
ActivationType active_gate) {
ActivationType active_gate, bool origin_mode) {
for (int b = 0; b < batch_size; b++) {
if (OpResetGrad::avx && !(frame_size & (8 - 1)) && (sizeof(T) == 4)) {
hl_avx_gru_backward_reset_grad(
op_reset_grad, value.gate_value, grad.gate_grad, value.prev_out_value,
grad.prev_out_grad, grad.reset_output_grad, frame_size, active_gate);
hl_avx_gru_backward_reset_grad(op_reset_grad, value.gate_value,
grad.gate_grad, value.prev_out_value,
grad.prev_out_grad, grad.reset_output_grad,
frame_size, active_gate, origin_mode);
} else {
hl_naive_gru_backward_reset_grad(
op_reset_grad, value.gate_value, grad.gate_grad, value.prev_out_value,
grad.prev_out_grad, grad.reset_output_grad, frame_size, active_gate);
grad.prev_out_grad, grad.reset_output_grad, frame_size, active_gate,
origin_mode);
}
value.gate_value += frame_size * 3;
......
paddle/fluid/operators/math/detail/gru_kernel.h
浏览文件 @ 9b16e540
......@@ -103,14 +103,24 @@ class gru_stateGrad {
HOSTDEVICE void operator()(T *value_update_gate, T *grad_update_gate,
T *value_frame_state, T *grad_frame_state,
T *value_prev_out, T *grad_prev_out,
T *grad_output, ActivationType act_input) {
*grad_update_gate = (*grad_output * (*value_frame_state));
*grad_update_gate -= (*grad_output * (*value_prev_out));
*grad_prev_out -= (*grad_output * (*value_update_gate));
*grad_prev_out += *grad_output;
T *grad_output, ActivationType act_input,
bool origin_mode) {
if (origin_mode) {
*grad_update_gate =
(*grad_output) * ((*value_prev_out) - (*value_frame_state));
*grad_prev_out += (*grad_output * (*value_update_gate));
*grad_frame_state = activation(
*grad_output * (static_cast<T>(1.0) - (*value_update_gate)),
*value_frame_state, act_input);
} else {
*grad_update_gate =
(*grad_output) * ((*value_frame_state) - (*value_prev_out));
*grad_prev_out +=
(*grad_output * (static_cast<T>(1.0) - *value_update_gate));
*grad_frame_state = activation(*grad_output * (*value_update_gate),
*value_frame_state, act_input);
}
}
#ifndef __NVCC__
#ifndef __AVX__
static const bool avx = false;
......@@ -121,7 +131,7 @@ class gru_stateGrad {
__m256 *value_frame_state,
__m256 *grad_frame_state, __m256 *value_prev_out,
__m256 *grad_prev_out, __m256 *grad_output,
ActivationType act_input) {
ActivationType act_input, bool origin_mode) {
*grad_update_gate = _mm256_mul_ps(*grad_output, *value_frame_state);
*grad_update_gate = _mm256_sub_ps(
*grad_update_gate, _mm256_mul_ps(*grad_output, *value_prev_out));
......@@ -143,7 +153,8 @@ class gru_resetGrad {
HOSTDEVICE void operator()(T *value_update_gate, T *grad_update_gate,
T *value_reset_gate, T *grad_reset_gate,
T *value_prev_out, T *grad_prev_out,
T *grad_reset_output, ActivationType act_gate) {
T *grad_reset_output, ActivationType act_gate,
bool origin_mode) {
*grad_reset_gate = (*grad_reset_output * (*value_prev_out));
*grad_prev_out += (*grad_reset_output * (*value_reset_gate));
*grad_update_gate =
......@@ -160,7 +171,7 @@ class gru_resetGrad {
__m256 *grad_update_gate, __m256 *value_reset_gate,
__m256 *grad_reset_gate, __m256 *value_prev_out,
__m256 *grad_prev_out, __m256 *grad_reset_output,
ActivationType act_gate) {
ActivationType act_gate, bool origin_mode) {
*grad_reset_gate = _mm256_mul_ps(*grad_reset_output, *value_prev_out);
*grad_prev_out = _mm256_add_ps(
*grad_prev_out, _mm256_mul_ps(*grad_reset_output, *value_reset_gate));
......
paddle/fluid/operators/math/gru_compute.cc
浏览文件 @ 9b16e540
......@@ -60,7 +60,8 @@ struct GRUUnitGradFunctor<platform::CPUDeviceContext, T> {
bool origin_mode) {
#ifndef __NVCC__
detail::backward_state_grad(detail::backward::gru_stateGrad<T>(), value,
grad, frame_size, batch_size, active_node);
grad, frame_size, batch_size, active_node,
origin_mode);
auto blas = math::GetBlas<platform::CPUDeviceContext, T>(context);
if (value.prev_out_value && grad.prev_out_grad) {
blas.GEMM(false, true, batch_size, frame_size, frame_size, 1,
......@@ -77,7 +78,8 @@ struct GRUUnitGradFunctor<platform::CPUDeviceContext, T> {
}
detail::backward_reset_grad(detail::backward::gru_resetGrad<T>(), value,
grad, frame_size, batch_size, active_gate);
grad, frame_size, batch_size, active_gate,
origin_mode);
if (grad.prev_out_grad && value.prev_out_value) {
blas.GEMM(false, true, batch_size, frame_size, frame_size * 2, 1,
grad.gate_grad, frame_size * 3, value.gate_weight,
......
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