提交 b2855761 编写于 作者: Z zhangyang0701 提交者: GitHub

Merge pull request #1402 from qnqinan/develop

add dw deconv with group in FPGA track fixed#1401
......@@ -151,6 +151,30 @@ void format_dwconv_filter(framework::Tensor *filter_tensor, float *scale_ptr) {
filter_tensor->reset_data_ptr(new_data);
}
void format_DWDconv_filter(framework::Tensor *filter_tensor, float *scale_ptr,
int stride) {
auto dims = filter_tensor->dims();
auto num = dims[0], height = dims[2], width = dims[3];
auto data_ptr = filter_tensor->data<float>();
size_t memory_size = num * height * width * sizeof(float);
auto new_data = (float *)fpga_malloc(memory_size); // NOLINT
fpga_copy(new_data, data_ptr, memory_size);
int hw = height * width;
deconv_filter::deconv_NC_convert(&new_data, num, 1, hw);
num = dims[1];
int channel = dims[0];
deconv_filter::DWDconv_format_filter(&new_data, num, channel, height, width,
scale_ptr, stride);
// framework::DDim dims_new =
// framework::make_ddim({num, 1, height, width});
// filter_tensor->Resize(dims_new);
filter_tensor->reset_data_ptr(new_data);
}
void format_fc_filter(framework::Tensor *filter_tensor, float max_value) {
filter_tensor->scale[0] = float(max_value / 127.0); // NOLINT
filter_tensor->scale[1] = float(127.0 / max_value); // NOLINT
......@@ -243,6 +267,17 @@ void format_dwconv_data(framework::Tensor *filter_tensor,
format_bias_array(bias_ptr, channel);
format_fp16_ofm(ofm_tensor);
}
void format_DWDeconv_data(framework::Tensor *filter_tensor,
framework::Tensor *ofm_tensor, float **bs_ptr,
int group, int sub_conv_n) {
int channel = ofm_tensor->dims()[1];
// dw-deconv
format_DWDconv_filter(
filter_tensor,
(reinterpret_cast<float *>(*bs_ptr) + sub_conv_n * channel), sub_conv_n);
format_bias_array(bs_ptr, channel);
format_fp16_ofm(ofm_tensor);
}
void expand_conv_arg(ConvArgs *arg) {
ConvArgs args = *arg;
......@@ -770,6 +805,7 @@ void fill_dwconv_arg(struct DWconvArgs *arg, framework::Tensor *input,
auto filter_ptr = filter->data<float>();
auto input_ptr = input->data<float>();
auto output_ptr = out->mutable_data<float>();
arg->sub_conv_num = 1;
arg->relu_enabled = relu_enabled;
arg->bias_address = bias_ptr;
arg->filter_address = filter_ptr;
......@@ -788,5 +824,109 @@ void fill_dwconv_arg(struct DWconvArgs *arg, framework::Tensor *input,
arg->output.scale_address = out->scale;
} // end dwconv arg fill
void fill_DWDeconv_arg(struct DWDeconvArgs *arg, framework::Tensor *input,
framework::Tensor *out, framework::Tensor *filter,
bool relu_enabled, int stride_h, int stride_w,
int padding_h, int padding_w, float *bias_ptr) {
auto filter_ptr = filter->data<float>();
auto input_ptr = input->data<float>();
auto output_ptr = out->mutable_data<float>();
auto deleter = [](void *p) { fpga_free(p); };
arg->group_num = (uint32_t)filter->dims()[0];
arg->sub_conv_num = (uint32_t)stride_w;
arg->filter_num = (uint32_t)filter->dims()[0];
int sub_conv_num = stride_w;
int sub_pad =
deconv_filter::deconv_calc_sub_pad((int)filter->dims()[3], // NOLINT
padding_w, stride_w);
auto sub_filter_width = (uint32_t)deconv_filter::deconv_get_sub_filter_axis(
(int)filter->dims()[3], stride_w); // NOLINT
auto sub_output_width = (uint32_t)deconv_filter::deconv_get_sub_out_axis(
(int)input->dims()[3], sub_pad, sub_filter_width); // NOLINT
auto sub_output_height = (uint32_t)deconv_filter::deconv_get_sub_out_axis(
(int)input->dims()[2], sub_pad, sub_filter_width); // NOLINT
arg->sub_output_width = (uint32_t)sub_output_width;
arg->sub_output_height = (uint32_t)sub_output_height;
arg->omit_size = (uint32_t)deconv_filter::deconv_get_omit(
stride_w, (int)filter->dims()[3], padding_w); // NOLINT
auto sub_channels = (int)input->dims()[1]; // NOLINT
uint32_t omit_size = arg->omit_size;
int real_out_width = sub_output_width * sub_conv_num - 2 * omit_size;
int real_out_height = sub_output_height * sub_conv_num - 2 * omit_size;
int sub_filter_num = sub_conv_num * (arg->filter_num);
framework::DDim dims_out_new = framework::make_ddim(
{1, arg->filter_num, real_out_height, real_out_width});
fpga::format_fp16_ofm(out, dims_out_new);
auto out_ptr = out->data<float>();
/*====For Addition
arg->output.address =
(half *)out_ptr + // NOLINT
omit_size * sizeof(half) *
(align_to_x(real_out_width * arg->filter_num, IMAGE_ALIGNMENT));
*/
arg->output.address = out_ptr;
arg->output.scale_address = out->scale;
int filter_offset = sub_filter_width * sub_filter_width *
align_to_x(sub_channels, FILTER_ELEMENT_ALIGNMENT) *
arg->sub_conv_num;
for (int i = 0; i < sub_conv_num; ++i) {
arg->dw_conv_args.push_back(std::make_shared<DWconvArgs>());
arg->dw_conv_args[i]->sub_conv_num = sub_conv_num;
arg->dw_conv_args[i]->relu_enabled = relu_enabled;
arg->dw_conv_args[i]->bias_address = bias_ptr;
arg->dw_conv_args[i]->filter_address =
fpga_malloc(filter_offset * sizeof(int16_t));
memcpy(arg->dw_conv_args[i]->filter_address,
(reinterpret_cast<half *>(filter_ptr) + i * filter_offset),
filter_offset * sizeof(int16_t));
arg->vector_dw_conv_space.push_back(std::shared_ptr<char>(
reinterpret_cast<char *>(arg->dw_conv_args[i]->filter_address),
deleter));
arg->dw_conv_args[i]->kernel.height = (uint32_t)sub_filter_width;
arg->dw_conv_args[i]->kernel.width = (uint32_t)sub_filter_width;
arg->dw_conv_args[i]->kernel.stride_h = (uint32_t)1;
arg->dw_conv_args[i]->kernel.stride_w = (uint32_t)1;
arg->dw_conv_args[i]->image.address = input_ptr;
arg->dw_conv_args[i]->image.channels = (uint32_t)input->dims()[1];
arg->dw_conv_args[i]->image.height = (uint32_t)input->dims()[2];
arg->dw_conv_args[i]->image.width = (uint32_t)input->dims()[3];
arg->dw_conv_args[i]->image.pad_height = sub_pad;
arg->dw_conv_args[i]->image.pad_width = sub_pad;
arg->dw_conv_args[i]->image.scale_address = input->scale;
arg->dw_conv_args[i]->output.address =
fpga_malloc(sub_output_height *
align_to_x(sub_output_width * sub_channels * sub_conv_num,
IMAGE_ALIGNMENT) *
sizeof(int16_t));
arg->dw_conv_args[i]->output.scale_address =
static_cast<float *>(fpga_malloc(2 * sizeof(float)));
arg->vector_dw_conv_space.push_back(std::shared_ptr<char>(
reinterpret_cast<char *>(arg->dw_conv_args[i]->output.address),
deleter));
arg->vector_dw_conv_space.push_back(std::shared_ptr<char>(
reinterpret_cast<char *>(arg->dw_conv_args[i]->output.scale_address),
deleter));
}
// arg->output.scale_address = out->scale;
} // end dwconv arg fill
} // namespace fpga
} // namespace paddle_mobile
......@@ -57,6 +57,10 @@ void fill_dwconv_arg(struct DWconvArgs* arg, framework::Tensor* input,
framework::Tensor* out, framework::Tensor* filter,
bool relu_enabled, int stride_h, int stride_w,
int padding_h, int padding_w, float* bias_ptr);
void fill_DWDeconv_arg(struct DWDeconvArgs* arg, framework::Tensor* input,
framework::Tensor* out, framework::Tensor* filter,
bool relu_enabled, int stride_h, int stride_w,
int padding_h, int padding_w, float* bs_ptr);
void format_deconv_filter(framework::Tensor* filter_tensor, float max_value,
int group_num, int stride);
......@@ -69,6 +73,10 @@ void format_deconv_data(framework::Tensor* filter_tensor,
void format_dwconv_data(framework::Tensor* filter_tensor,
framework::Tensor* ofm_tensor, float* scale_ptr,
float** bias_ptr);
void format_DWDeconv_data(framework::Tensor* filter_tensor,
framework::Tensor* ofm_tensor, float** bs_ptr,
int group, int sub_conv_n);
template <typename Dtype>
void savefile(std::string filename, void* buffer, int dataSize, Dtype tmp) {
float data;
......
......@@ -21,15 +21,6 @@ limitations under the License. */
#include "fpga/V1/api.h"
// #include "fpga_api.h"
// just for test
//#include <string>
//#include "deconv.h"
//#include "deconv_api.h"
// using namespace std;
// using namespace paddle_mobile::fpga;
// using namespace baidu::fpga::deconv::api;
// namespace api = baidu::fpga::deconv::api;
namespace paddle_mobile {
namespace fpga {
namespace deconv_filter {
......@@ -42,7 +33,8 @@ void deconv_inverse_filter(float** data_in, int num, int channel, int width,
float* tmp = *data_in;
int data_size = num * channel * width * height;
int hw_len = height * width;
auto tmp_data = (float*)fpga_malloc(data_size * sizeof(float));
auto tmp_data =
reinterpret_cast<float*>(fpga_malloc(data_size * sizeof(float)));
for (int i = 0; i < num; ++i) {
for (int j = 0; j < channel; ++j) {
for (int k = 0; k < hw_len; ++k) {
......@@ -97,9 +89,10 @@ int deconv_get_omit(int stride, int filter_width, int pad) {
return (stride - idx);
}
void deconv_get_sub_filter(char** data_in, int height, int width,
int sub_conv_n, int kernel_num, int channel) {
char* ptr_tmp = *data_in;
template <typename T>
void deconv_get_sub_filter(T** data_in, int height, int width, int sub_conv_n,
int kernel_num, int channel) {
T* ptr_tmp = *data_in;
int sub_num = kernel_num * sub_conv_n;
int sub_h = height / sub_conv_n;
int sub_w = width / sub_conv_n;
......@@ -107,7 +100,8 @@ void deconv_get_sub_filter(char** data_in, int height, int width,
int sub_filter_size =
kernel_num * sub_h * sub_w * channel * sub_conv_n * sub_conv_n;
char* ptr_sub_filter = (char*)fpga_malloc(sub_filter_size * sizeof(char));
T* ptr_sub_filter =
reinterpret_cast<T*>(fpga_malloc(sub_filter_size * sizeof(T)));
for (int idx = 0; idx < sub_conv_n; ++idx) {
for (int nn = 0; nn < sub_num; ++nn) {
int ni = nn % kernel_num;
......@@ -124,7 +118,7 @@ void deconv_get_sub_filter(char** data_in, int height, int width,
fpga_copy(
ptr_sub_filter + idx * sub_h * sub_w * channel * sub_num + sidx,
(*data_in) + kidx, channel * sizeof(char));
(*data_in) + kidx, channel * sizeof(T));
// for (int cc =0; cc < channel; ++cc) {
// ptr_sub_filter[idx*sub_h*sub_w*channel*sub_num + sidx + cc] =
// (*data_in)[kidx + cc];
......@@ -140,7 +134,7 @@ void deconv_get_sub_filter(char** data_in, int height, int width,
void deconv_NC_convert(float** filter_in, int kernel_num, int channels,
int hw) {
float* tmp = *filter_in;
float* ptr_filter = (float*)(paddle_mobile::fpga::fpga_malloc(
float* ptr_filter = reinterpret_cast<float*>(paddle_mobile::fpga::fpga_malloc(
hw * kernel_num * channels * sizeof(float)));
for (int c = 0; c < channels; ++c) {
......@@ -188,7 +182,8 @@ void deconv_format_filter(float** data_in, int num, int channel, int height,
result2);
}*/
deconv_get_sub_filter(quantize_data, height, width, stride, num, channel);
deconv_get_sub_filter<char>(quantize_data, height, width, stride, num,
channel);
/*{
char result2 = (char)0;
string filename = "sub_filter_filter_data";
......@@ -212,10 +207,12 @@ void deconv_format_filter(float** data_in, int num, int channel, int height,
((residual == 0) ? div_num : (div_num - 1)) +
align_to_x(residual, FILTER_NUM_ALIGNMENT);
char** ptr_ptr_data = (char**)fpga_malloc(sub_conv_n * sizeof(char*));
char** ptr_ptr_data =
reinterpret_cast<char**>(fpga_malloc(sub_conv_n * sizeof(char*)));
int origin_offset = sub_chw * sub_num;
for (int i = 0; i < sub_conv_n; ++i) {
(ptr_ptr_data)[i] = (char*)fpga_malloc(origin_offset * sizeof(char));
(ptr_ptr_data)[i] =
reinterpret_cast<char*>(fpga_malloc(origin_offset * sizeof(char)));
fpga_copy((ptr_ptr_data)[i], (*quantize_data) + origin_offset * i,
origin_offset * sizeof(char));
......@@ -233,8 +230,8 @@ void deconv_format_filter(float** data_in, int num, int channel, int height,
int align_offset =
align_to_x(sub_chw, FILTER_ELEMENT_ALIGNMENT) * num_after_alignment;
char* ptr_space = (char*)fpga_malloc(sub_conv_n * align_offset *
sizeof(char)); // continuous space
char* ptr_space = reinterpret_cast<char*>(fpga_malloc(
sub_conv_n * align_offset * sizeof(char))); // continuous space
for (int i = 0; i < sub_conv_n; ++i) {
char* ptr_tmp = (ptr_ptr_data)[i];
......@@ -251,7 +248,7 @@ void deconv_format_filter(float** data_in, int num, int channel, int height,
fpga_copy(ptr_space + i * align_offset, ptr_tmp, align_offset);
fpga_free(ptr_tmp);
}
*data_in = (float*)ptr_space;
*data_in = reinterpret_cast<float*>(ptr_space);
/* {
char result2 = (char)0;
......@@ -262,6 +259,22 @@ void deconv_format_filter(float** data_in, int num, int channel, int height,
fpga_flush(ptr_space, sub_conv_n * align_offset * sizeof(char));
}
void DWDconv_format_filter(float** data_in, int num, int channel, int height,
int width, float* scale_ptr, int stride) {
deconv_inverse_filter(data_in, num, channel, width, height);
filter::quantize_to_fp16(data_in, channel, height, width, scale_ptr);
int16_t** quantize_data = (int16_t**)data_in; // NOLINT
filter::convert_to_hwn(quantize_data, channel, height, width);
deconv_get_sub_filter<int16_t>(quantize_data, height, width, stride, num,
channel);
filter::align_element_n(quantize_data, channel, height, width);
fpga_flush(*quantize_data, align_to_x(channel, FILTER_ELEMENT_ALIGNMENT) *
height * width * sizeof(int16_t));
}
} // namespace deconv_filter
} // namespace fpga
} // namespace paddle_mobile
......@@ -24,11 +24,15 @@ int deconv_calc_sub_pad(int filter_axis, int pad, int stride);
int deconv_get_sub_filter_axis(int filter_axis, int stride);
int deconv_get_sub_out_axis(int image_axis, int sub_pad, int sub_filter_axis);
int deconv_get_omit(int stride, int filter_width, int pad);
void deconv_get_sub_filter(char** data_in, int height, int width,
int sub_conv_n, int kernel_num, int channel);
template <typename T>
void deconv_get_sub_filter(T** data_in, int height, int width, int sub_conv_n,
int kernel_num, int channel);
void deconv_format_filter(float** data_in, int num, int channel, int height,
int width, int group_num, float max, int stride);
void deconv_NC_convert(float** filter_in, int kernel_num, int channels, int hw);
void DWDconv_format_filter(float** data_in, int num, int channel, int height,
int width, float* scale_ptr, int stride);
} // namespace deconv_filter
} // namespace fpga
......
......@@ -346,6 +346,16 @@ void format_dwconv_filter(float **data_in, int num, int height, int width,
fpga_flush(*quantize_data, align_to_x(num, FILTER_ELEMENT_ALIGNMENT) *
height * width * sizeof(int16_t));
}
void format_DWDeconv_filter(float **data_in, int num, int height, int width,
float *scale_ptr) {
quantize_to_fp16(data_in, num, height, width, scale_ptr);
int16_t **quantize_data = (int16_t **)data_in; // NOLINT
convert_to_hwn(quantize_data, num, height, width);
align_element_n(quantize_data, num, height, width);
fpga_flush(*quantize_data, align_to_x(num, FILTER_ELEMENT_ALIGNMENT) *
height * width * sizeof(int16_t));
}
} // namespace filter
} // namespace fpga
} // namespace paddle_mobile
......@@ -18,7 +18,6 @@ limitations under the License. */
#include "fpga/V1/image.h"
#include "fpga/common/config.h"
#include "fpga/common/driver.h"
#ifdef COST_TIME_PRINT
#include <sys/time.h>
#include <time.h>
......@@ -163,6 +162,7 @@ using namespace std; // NOLINT
#define REG_DWCONV_FILTER_BASE_ADDR 0xe08
#define REG_DWCONV_FILTER_SHAPE 0xe10
#define REG_DWCONV_FILTER_N_ALIGN 0xe18
#define REG_DWCONV_FILTER_SUBNUMBER 0xe20
#define REG_DWCONV_CMD 0xe00
int ComputeFpgaConv(const struct SplitConvArgs &args) {
......@@ -591,6 +591,20 @@ int PerformBypass(const struct BypassArgs &args) {
return 0;
} // PerformBypass
uint64_t FPGAVersion() {
#ifdef FPGA_PRINT_MODE
DLOG << "=============ComputeFpgaBypass===========";
#endif
#ifdef PADDLE_MOBILE_ZU5
uint64_t fpga_ver = 0;
pthread_mutex_lock(&g_fpgainfo.pe_data->mutex);
fpga_ver = reg_readq(REG_HARDWARE_STATUS);
pthread_mutex_unlock(&g_fpgainfo.pe_data->mutex);
return fpga_ver;
#endif
return 0;
} // FPGAVersion
int ComputeFPGAConcat(const struct ConcatArgs &args) {
#ifdef FPGA_PRINT_MODE
DLOG << "=============ComputeFpgaConcat===========";
......@@ -655,6 +669,45 @@ void deconv_post_process(const struct DeconvArgs &args) {
fpga_flush(args.output.address,
num * align_deconv_row_len * deconv_h * sizeof(int16_t));
}
void DWDeconv_post_process(const struct DWDeconvArgs &args) {
int sub_conv_n = args.sub_conv_num;
int sub_height = args.sub_output_height;
int sub_width = args.sub_output_width;
int omit_size = args.omit_size;
int channel = args.filter_num;
int num = 1;
int origin_h = sub_height * sub_conv_n;
int origin_w = sub_width * sub_conv_n;
int align_origin_w = align_to_x(origin_w * channel, IMAGE_ALIGNMENT);
int deconv_h = origin_h - 2 * omit_size;
int deconv_w = origin_w - 2 * omit_size;
int deconv_row_len = deconv_w * channel;
int align_deconv_row_len = align_to_x(deconv_row_len, IMAGE_ALIGNMENT);
for (int idx = 0; idx < sub_conv_n; ++idx) {
paddle_mobile::fpga::fpga_invalidate(
args.dw_conv_args[idx]->output.address,
align_origin_w * origin_h * sizeof(int16_t));
}
int deconv_idx = 0;
for (int nn = 0; nn < num; ++nn) {
for (int hh = 0; hh < origin_h; ++hh) {
int hx = (hh % sub_conv_n);
auto sub_t = (int16_t *)(args.dw_conv_args[sub_conv_n - hx - 1] // NOLINT
->output.address);
int hi = (hh / sub_conv_n);
if ((hh < omit_size) || (hh >= (origin_h - omit_size))) continue;
int sidx = (nn * origin_h * align_origin_w + hi * align_origin_w +
omit_size * channel);
fpga_copy((int16_t *)(args.output.address) + deconv_idx, // NOLINT
sub_t + sidx, sizeof(int16_t) * deconv_row_len); // NOLINT
deconv_idx += align_deconv_row_len;
}
}
fpga_flush(args.output.address,
num * align_deconv_row_len * deconv_h * sizeof(int16_t));
}
int ComputeFpgaDeconv(const struct DeconvArgs &args) {
#ifdef FPGA_PRINT_MODE
......@@ -792,17 +845,21 @@ int ComputeDWConv(const struct DWconvArgs &args) {
align_to_x((uint64_t)args.image.channels, IMAGE_ALIGNMENT);
uint64_t filter_amount_per_row_align =
filter_N_align * (uint64_t)args.kernel.width;
uint64_t filter_amount_align = filter_N_align * (uint64_t)args.kernel.width *
(uint64_t)args.kernel.height;
uint64_t sub_filter_amount_align = filter_N_align *
(uint64_t)args.kernel.width *
(uint64_t)args.kernel.height;
uint64_t filter_amount_align =
sub_filter_amount_align * (uint64_t)args.sub_conv_num;
uint32_t output_height = (uint32_t)(
(args.image.height + args.image.pad_height * 2 - args.kernel.height) /
args.kernel.stride_h +
1);
uint32_t output_width = (uint32_t)(
(args.image.width + args.image.pad_width * 2 - args.kernel.width) /
args.kernel.stride_w +
1);
((args.image.width + args.image.pad_width * 2 - args.kernel.width) /
args.kernel.stride_w +
1) *
args.sub_conv_num);
uint64_t image_amount_per_row =
align_to_x((uint64_t)args.image.width * (uint64_t)args.image.channels,
......@@ -845,12 +902,15 @@ int ComputeDWConv(const struct DWconvArgs &args) {
/*restart scale*/
reg_writeq(output_scale, REG_SCALE_PARAMETER);
reg_writeq(image_physical_address, REG_POOLING_IMAGE_BASE_ADDR);
reg_writeq(output_physical_address, REG_POOLING_RESULT_BASE_ADDR);
reg_writeq((bias_physical_address << 32 | filter_physical_address),
REG_DWCONV_FILTER_BASE_ADDR);
reg_writeq(filter_amount_per_row_align | (filter_amount_align << 32),
REG_DWCONV_FILTER_SHAPE);
reg_writeq(sub_filter_amount_align | (((uint64_t)args.sub_conv_num) << 32),
REG_DWCONV_FILTER_SUBNUMBER);
reg_writeq(filter_N_align, REG_DWCONV_FILTER_N_ALIGN);
reg_writeq(
......@@ -904,10 +964,88 @@ int ComputeDWConv(const struct DWconvArgs &args) {
output_scale = reg_readq(REG_SCALE_PARAMETER);
output_scale = (output_scale << 32) | (output_scale >> 32);
fpga_copy(args.output.scale_address, &output_scale, sizeof(float) * 2);
DLOG << "output_scale:" << output_scale;
pthread_mutex_unlock(&g_fpgainfo.pe_data->mutex);
return ret;
#endif
return 0;
}
int ComputeDWDeconv(const struct DWDeconvArgs &args) {
#ifdef FPGA_PRINT_MODE
DLOG << "=============ComputeFPGADeConv===========";
DLOG << " filter_num:" << args.filter_num
<< " group_num:" << args.group_num << "omit_size:" << args.omit_size
<< "sub_output_width: " << args.sub_output_width
<< "sub_output_height: " << args.sub_output_height
<< " sub_conv_num:" << args.sub_conv_num;
DLOG << "args.output.address: " << args.output.address
<< "args.output.scale_address: " << args.output.scale_address;
#endif
int sub_conv_num = args.sub_conv_num;
#ifdef COST_TIME_PRINT
timeval start, end;
long dif_sec, dif_usec; // NOLINT
#endif
for (int i = 0; i < sub_conv_num; i++) {
#ifdef COST_TIME_PRINT
gettimeofday(&start, NULL);
#endif
ComputeDWConv(*args.dw_conv_args[i]);
#ifdef COST_TIME_PRINT
gettimeofday(&end, NULL);
dif_sec = end.tv_sec - start.tv_sec;
dif_usec = end.tv_usec - start.tv_usec;
std::cout << "deconv basic_conv: " << i << " times: "
<< " cost time: " << (dif_sec * 1000000 + dif_usec) << "us"
<< std::endl;
#endif
}
if (sub_conv_num > 1) {
float max_scale = -1.0f;
#ifdef COST_TIME_PRINT
gettimeofday(&start, NULL);
#endif
for (int i = 0; i < sub_conv_num; i++) {
paddle_mobile::fpga::fpga_invalidate(
args.dw_conv_args[i]->output.scale_address, 2 * sizeof(float));
float ptr_scale = (args.dw_conv_args[i]->output.scale_address)[0];
if (ptr_scale > max_scale) {
args.output.scale_address[0] = ptr_scale;
args.output.scale_address[1] =
(args.dw_conv_args[i]->output.scale_address)[1];
}
}
#ifdef COST_TIME_PRINT
gettimeofday(&end, NULL);
dif_sec = end.tv_sec - start.tv_sec;
dif_usec = end.tv_usec - start.tv_usec;
std::cout << "deconv scale "
<< " cost time: " << (dif_sec * 1000000 + dif_usec) << "us"
<< std::endl;
#endif
}
#ifdef COST_TIME_PRINT
gettimeofday(&start, NULL);
#endif
DWDeconv_post_process(args);
#ifdef COST_TIME_PRINT
gettimeofday(&end, NULL);
dif_sec = end.tv_sec - start.tv_sec;
dif_usec = end.tv_usec - start.tv_usec;
std::cout << "deconv_post_process "
<< " cost time: " << (dif_sec * 1000000 + dif_usec) << "us"
<< std::endl;
#endif
return 0;
} // ComputeFpgaDeconv
} // namespace fpga
} // namespace paddle_mobile
......@@ -76,7 +76,7 @@ int32_t convertmantissa(int32_t i) {
}
float fp16_2_fp32(int16_t fp16_num) {
int16_t se_fp16 = fp16_num >> 10;
int16_t se_fp16 = (fp16_num >> 10) & 0x3f;
int16_t m_fp16 = fp16_num & 0x3ff;
int32_t e_fp32 = 0;
int16_t offset = 0;
......@@ -94,7 +94,7 @@ float fp16_2_fp32(int16_t fp16_num) {
e_fp32 = 0x80000000;
offset = 0;
} else if (se_fp16 < 63) {
e_fp32 = 0x80000000 + (se_fp16 - 32) << 23;
e_fp32 = 0x80000000 + ((se_fp16 - 32) << 23);
offset = 1024;
} else { // se_fp16 == 63
e_fp32 = 0xC7800000;
......
......@@ -229,6 +229,7 @@ struct DeconvArgs {
std::vector<std::shared_ptr<SplitConvArgs>> split_conv_args;
};
struct DWconvArgs {
uint32_t sub_conv_num;
bool relu_enabled;
void* bias_address;
void* filter_address;
......@@ -236,6 +237,19 @@ struct DWconvArgs {
struct ImageInputArgs image;
struct ImageOutputArgs output;
};
struct DWDeconvArgs {
uint32_t sub_conv_num;
uint32_t group_num;
uint32_t filter_num;
uint32_t omit_size;
uint32_t sub_output_width;
uint32_t sub_output_height;
struct ImageOutputArgs output;
std::vector<std::shared_ptr<DWconvArgs>> dw_conv_args;
std::vector<std::shared_ptr<char>> vector_dw_conv_space;
};
// static inline int align_to_x(int num, int x) { return (num + x - 1) / x * x;
// }
static inline uint32_t align_to_x(int64_t num, int64_t x) {
......
......@@ -18,6 +18,7 @@ limitations under the License. */
namespace paddle_mobile {
namespace fpga {
uint64_t FPGAVersion();
int PerformBypass(const struct BypassArgs& args);
int ComputeBasicConv(const struct ConvArgs& args);
int ComputeFpgaPool(const struct PoolingArgs& args);
......@@ -28,5 +29,7 @@ int ComputeFPGAConcat(const struct ConcatArgs& args);
int ComputeFPGASplit(const struct SplitArgs& args);
int ComputeFpgaDeconv(const struct DeconvArgs& args);
int ComputeDWConv(const struct DWconvArgs& args);
int ComputeDWDeconv(const struct DWDeconvArgs& args);
} // namespace fpga
} // namespace paddle_mobile
......@@ -49,13 +49,23 @@ bool DeconvAddKernel<FPGA, float>::Init(FusionDeconvAddParam<FPGA> *param) {
"filter width should be equal to filter height ");
PADDLE_MOBILE_ENFORCE(((filter->dims()[2] % param->Strides()[0]) == 0),
"filter axis should be the multiple of stride axis ");
fpga::format_deconv_data(filter, out, &bs_ptr, param->Groups(), sub_conv_n);
fpga::DeconvArgs deconv_arg = {0};
fpga::fill_deconv_arg(&deconv_arg, input, out, filter, relu_enabled,
param->Groups(), param->Strides()[0],
param->Strides()[1], param->Paddings()[0],
param->Paddings()[1], bs_ptr);
param->SetFpgaArgs(deconv_arg);
if (param->Groups() == channel) {
fpga::format_DWDeconv_data(filter, out, &bs_ptr, param->Groups(),
sub_conv_n);
fpga::DWDeconvArgs DWDeconv_arg = {0};
fpga::fill_DWDeconv_arg(&DWDeconv_arg, input, out, filter, relu_enabled,
param->Strides()[0], param->Strides()[1],
param->Paddings()[0], param->Paddings()[1], bs_ptr);
param->SetFpgaArgs(DWDeconv_arg);
} else {
fpga::format_deconv_data(filter, out, &bs_ptr, param->Groups(), sub_conv_n);
fpga::DeconvArgs deconv_arg = {0};
fpga::fill_deconv_arg(&deconv_arg, input, out, filter, relu_enabled,
param->Groups(), param->Strides()[0],
param->Strides()[1], param->Paddings()[0],
param->Paddings()[1], bs_ptr);
param->SetFpgaArgs(deconv_arg);
}
return true;
}
......@@ -63,7 +73,11 @@ bool DeconvAddKernel<FPGA, float>::Init(FusionDeconvAddParam<FPGA> *param) {
template <>
void DeconvAddKernel<FPGA, float>::Compute(
const FusionDeconvAddParam<FPGA> &param) {
fpga::ComputeFpgaDeconv(param.FpgaArgs());
if (param.Groups() == param.Output()->dims()[1]) {
fpga::ComputeDWDeconv(param.FpgaDWDconvArgs());
} else {
fpga::ComputeFpgaDeconv(param.FpgaArgs());
}
}
} // namespace operators
......
......@@ -50,20 +50,35 @@ bool DeconvAddReluKernel<FPGA, float>::Init(
"filter width should be equal to filter height ");
PADDLE_MOBILE_ENFORCE(((filter->dims()[2] % param->Strides()[0]) == 0),
"filter axis should be the multiple of stride axis ");
fpga::format_deconv_data(filter, out, &bs_ptr, param->Groups(), sub_conv_n);
fpga::DeconvArgs deconv_arg = {0};
fpga::fill_deconv_arg(&deconv_arg, input, out, filter, relu_enabled,
param->Groups(), param->Strides()[0],
param->Strides()[1], param->Paddings()[0],
param->Paddings()[1], bs_ptr);
param->SetFpgaArgs(deconv_arg);
if (param->Groups() == channel) {
fpga::format_DWDeconv_data(filter, out, &bs_ptr, param->Groups(),
sub_conv_n);
fpga::DWDeconvArgs DWDeconv_arg = {0};
fpga::fill_DWDeconv_arg(&DWDeconv_arg, input, out, filter, relu_enabled,
param->Strides()[0], param->Strides()[1],
param->Paddings()[0], param->Paddings()[1], bs_ptr);
param->SetFpgaArgs(DWDeconv_arg);
} else {
fpga::format_deconv_data(filter, out, &bs_ptr, param->Groups(), sub_conv_n);
fpga::DeconvArgs deconv_arg = {0};
fpga::fill_deconv_arg(&deconv_arg, input, out, filter, relu_enabled,
param->Groups(), param->Strides()[0],
param->Strides()[1], param->Paddings()[0],
param->Paddings()[1], bs_ptr);
param->SetFpgaArgs(deconv_arg);
}
return true;
}
template <>
void DeconvAddReluKernel<FPGA, float>::Compute(
const FusionDeconvAddReluParam<FPGA> &param) {
fpga::ComputeFpgaDeconv(param.FpgaArgs());
// fpga::ComputeFpgaDeconv(param.FpgaArgs());
if (param.Groups() == param.Output()->dims()[1]) {
fpga::ComputeDWDeconv(param.FpgaDWDconvArgs());
} else {
fpga::ComputeFpgaDeconv(param.FpgaArgs());
}
}
} // namespace operators
......
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#ifdef SIGMOID_OP
#include "operators/kernel/activation_kernel.h"
namespace paddle_mobile {
namespace operators {
using framework::DDim;
using framework::Tensor;
template <>
bool SigmoidKernel<FPGA, float>::Init(SigmoidParam<FPGA> *param) {
auto input = const_cast<Tensor *>(param->InputX());
auto input_ptr = input->data<float>();
auto out = param->Out();
fpga::format_fp32_ofm(out);
auto float_input = new Tensor;
if (input->dims().size() == 2) {
float_input->mutable_data<float>({1, input->dims()[1]});
} else if (input->dims().size() == 4) {
float_input->mutable_data<float>(
{1, input->dims()[2], input->dims()[3], input->dims()[1]});
} else {
DLOG << "wrong dimension of softmax input";
}
fpga::format_fp32_ofm(float_input);
fpga::BypassArgs args = {fpga::DATA_TYPE_FP16};
args.input_layout_type = fpga::LAYOUT_HWC;
args.output_layout_type = fpga::LAYOUT_CHW;
args.input_data_type = fpga::DATA_TYPE_FP16;
args.output_data_type = fpga::DATA_TYPE_FP32;
args.image.address = input_ptr;
args.image.height =
(input->dims().size() == 4) ? (uint32_t)input->dims()[2] : 1;
args.image.width =
(input->dims().size() == 4) ? (uint32_t)input->dims()[3] : 1;
args.image.channels = (uint32_t)input->dims()[1];
args.output.address = float_input->data<float>();
args.output.scale_address = float_input->scale;
param->SetFloatInput(float_input);
param->SetFpgaArgs(args);
return true;
}
template <typename T>
T Sigmoid(const T a) {
T tmp = -1.0f * a;
return (1.0 / (1.0 + exp(tmp)));
}
template <typename T>
void sigmoidFuntor(Tensor *input, Tensor *output) {
auto *input_ptr = input->data<T>();
auto *output_ptr = output->mutable_data<T>();
for (int i = 0; i < input->numel(); i++) {
*(output_ptr + i) = Sigmoid<T>(*(input_ptr + i));
}
}
template <>
void SigmoidKernel<FPGA, float>::Compute(const SigmoidParam<FPGA> &param) {
Tensor *in_x = param.FloatInput();
Tensor *out = param.Out();
fpga::PerformBypass(param.FpgaArgs());
fpga::fpga_invalidate((void *)in_x->data<float>(), // NOLINT
in_x->numel() * sizeof(float));
// TODO: In general case, 0 should be squeezed before softmax input // NOLINT
sigmoidFuntor<float>(in_x, out);
fpga::fpga_flush(out->data<float>(), out->memory_size());
}
} // namespace operators
} // namespace paddle_mobile
#endif
......@@ -1078,6 +1078,20 @@ class SigmoidParam : public OpParam {
private:
RType *input_x_;
RType *out_;
#ifdef PADDLE_MOBILE_FPGA
private:
std::shared_ptr<RType> float_input_x_;
fpga::BypassArgs fpga_bypass_args;
public:
RType *FloatInput() const {
return float_input_x_ == nullptr ? input_x_ : float_input_x_.get();
}
void SetFloatInput(Tensor *input) { float_input_x_.reset(input); }
const fpga::BypassArgs &FpgaArgs() const { return fpga_bypass_args; }
void SetFpgaArgs(const fpga::BypassArgs &args) { fpga_bypass_args = args; }
#endif
};
#endif
......@@ -2357,10 +2371,17 @@ class ConvTransposeParam : public OpParam {
private:
fpga::DeconvArgs fpga_conv_args;
fpga::DWDeconvArgs fpga_DWDeconv_args;
public:
const fpga::DeconvArgs &FpgaArgs() const { return fpga_conv_args; }
const fpga::DWDeconvArgs &FpgaDWDconvArgs() const {
return fpga_DWDeconv_args;
}
void SetFpgaArgs(const fpga::DeconvArgs &args) { fpga_conv_args = args; }
void SetFpgaArgs(const fpga::DWDeconvArgs &args) {
fpga_DWDeconv_args = args;
}
#endif
};
......
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