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Commit f84274d5 authored by Hashim Sharif's avatar Hashim Sharif
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Adding necessary deviceToHostCopy(tensor) calls for CPU tensor RT routines

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hpvm/projects/hpvm-tensor-rt/tensor_runtime/src/tensor_cpu_runtime.cc
+ 67
− 23
View file @ f84274d5
......@@ -38,6 +38,7 @@
#include "tensor_runtime.h"
#include "tensor_cpu_runtime.h"
#include "approx_api.h"
#include "tensor_utils.h"
void llvm_hpvm_initTensorRtCPU() {
......@@ -56,6 +57,7 @@ void *tensorRegularConvolutionCPU(void *input_ptr, void *filter_ptr,
int vertical_pad, int horizontal_pad,
int vertical_stride, int horizontal_stride,
int conv_mode, int compute_precision) {
Tensor *input = (Tensor *)input_ptr;
Tensor *filter = (Tensor *)filter_ptr;
......@@ -135,12 +137,14 @@ void *tensorRegularConvolutionCPU(void *input_ptr, void *filter_ptr,
return output;
}
void *tensorRegularFilterSamplingConvolutionCPU(
void *input_ptr, void *filter_ptr, int vertical_pad, int horizontal_pad,
int vertical_stride, int horizontal_stride, int conv_mode,
int compute_precision, int skip_every, int start) {
Tensor *input = (Tensor *)input_ptr;
Tensor *filter = (Tensor *)filter_ptr;
void *tensorRegularFilterSamplingConvolutionCPU(void *input_ptr, void *filter_ptr,
int vertical_pad, int horizontal_pad,
int vertical_stride, int horizontal_stride,
int conv_mode, int compute_precision,
int skip_every, int start) {
Tensor *input = (Tensor *) input_ptr;
Tensor *filter = (Tensor *) filter_ptr;
float *__restrict__ host_image = (float *)input->host_data;
float *__restrict__ host_filter = (float *)filter->host_data;
......@@ -259,10 +263,12 @@ void *tensorRegularFilterSamplingConvolutionCPU(
return output;
}
void *tensorIrregularFilterSamplingConvolutionCPU(
void *input_ptr, void *filter_ptr, int vertical_pad, int horizontal_pad,
int vertical_stride, int horizontal_stride, int conv_mode,
int compute_precision, int skip_every, int start) {
void *tensorIrregularFilterSamplingConvolutionCPU(void *input_ptr, void *filter_ptr,
int vertical_pad, int horizontal_pad,
int vertical_stride, int horizontal_stride,
int conv_mode, int compute_precision,
int skip_every, int start) {
Tensor *input = (Tensor *)input_ptr;
Tensor *filter = (Tensor *)filter_ptr;
......@@ -665,20 +671,24 @@ void *tensorConvApproxCPU(void *input_ptr, void *filter_ptr, int vertical_pad,
int horizontal_stride, int conv_mode,
int compute_precision, int row, int col,
int skip_every, int start) {
Tensor *input = (Tensor *) input_ptr;
Tensor *filter = (Tensor *) filter_ptr;
deviceToHostCopy(input);
deviceToHostCopy(filter);
if (row > 1) {
//printf("ROW PERFORATION\n");
return tensorRowPerfConvolutionCPU(
input_ptr, filter_ptr, vertical_pad, horizontal_pad, vertical_stride,
horizontal_stride, conv_mode, compute_precision, row, start);
}
if (col > 1) {
//printf("COL PERFORATION\n");
return tensorColPerfConvolutionCPU(
input_ptr, filter_ptr, vertical_pad, horizontal_pad, vertical_stride,
horizontal_stride, conv_mode, compute_precision, col, start);
}
if (skip_every > 1) {
//printf("INPUT FILTERING\n");
Tensor *filter = (Tensor *)filter_ptr;
const int kernel_height = filter->dims.dim_sizes[2];
......@@ -707,6 +717,9 @@ void *tensorConvCutlassCPU(void *input_ptr, void *filter_ptr, int vertical_pad,
Tensor *input = (Tensor *)input_ptr;
Tensor *filter = (Tensor *)filter_ptr;
deviceToHostCopy(input);
deviceToHostCopy(filter);
float *__restrict__ host_image = (float *)input->host_data;
float *__restrict__ host_filter = (float *)filter->host_data;
......@@ -783,8 +796,12 @@ void *tensorConvCutlassCPU(void *input_ptr, void *filter_ptr, int vertical_pad,
}
void *tensorAddCPU(void *x_ptr, void *bias_ptr) {
Tensor *x = (Tensor *)x_ptr;
Tensor *bias = (Tensor *)bias_ptr;
Tensor *x = (Tensor *) x_ptr;
Tensor *bias = (Tensor *) bias_ptr;
deviceToHostCopy(x);
deviceToHostCopy(bias);
float *__restrict__ x_data = (float *)x->host_data;
float *__restrict__ bias_data = (float *)bias->host_data;
......@@ -793,6 +810,7 @@ void *tensorAddCPU(void *x_ptr, void *bias_ptr) {
int h = x->dims.dim_sizes[2];
int w = x->dims.dim_sizes[3];
if (x->num_elems == bias->num_elems) {
int const1 = c * h * w;
int const2 = h * w;
......@@ -824,6 +842,7 @@ void *tensorAddCPU(void *x_ptr, void *bias_ptr) {
}
}
return x;
}
......@@ -835,6 +854,8 @@ void *tensorPoolingCPU(void *input_ptr, int poolFunction, int window_height,
int vertical_stride, int horizontal_stride) {
Tensor *input = (Tensor *)input_ptr;
deviceToHostCopy(input);
float *__restrict__ input_data = (float *)input->host_data;
int batch_size = input->dims.dim_sizes[0];
......@@ -929,13 +950,15 @@ void *tensorPoolingCPU(void *input_ptr, int poolFunction, int window_height,
}
void *tensorTanhCPU(void *input_ptr) {
Tensor *input = (Tensor *)input_ptr;
Tensor *input = (Tensor *)input_ptr;
deviceToHostCopy(input);
float *input_data = (float *)input->host_data;
size_t num_elems = input->num_elems;
omp_set_num_threads(4);
#pragma omp parallel for
#pragma omp parallel for
for (size_t i = 0; i < num_elems; i++) {
input_data[i] = tanhf(input_data[i]);
}
......@@ -944,9 +967,13 @@ void *tensorTanhCPU(void *input_ptr) {
}
void *tensorGemmCPU(void *lhs_ptr, void *rhs_ptr) {
Tensor *lhs = (Tensor *)lhs_ptr;
Tensor *rhs = (Tensor *)rhs_ptr;
deviceToHostCopy(lhs);
deviceToHostCopy(rhs);
int m = lhs->dims.dim_sizes[0];
int n = rhs->dims.dim_sizes[rhs->dims.num_dims - 1]; // output neurons
......@@ -963,6 +990,7 @@ void *tensorGemmCPU(void *lhs_ptr, void *rhs_ptr) {
}
float *tran_rhs = (float *)malloc(sizeof(float) * k * n);
omp_set_num_threads(4);
#pragma omp parallel for simd
for (int l = 0; l < k; l++) {
for (int j = 0; j < n; j++) {
......@@ -986,8 +1014,11 @@ void *tensorGemmCPU(void *lhs_ptr, void *rhs_ptr) {
}
void *tensorSoftmaxCPU(void *input_ptr) {
Tensor *input = (Tensor *)input_ptr;
deviceToHostCopy(input);
float *logits = (float *)input->host_data;
int n = input->dims.dim_sizes[0];
int c = input->dims.dim_sizes[1];
......@@ -1016,12 +1047,19 @@ void *tensorSoftmaxCPU(void *input_ptr) {
void *tensorBatchNormCPU(void *input_ptr, void *gamma_ptr, void *beta_ptr,
void *mean_ptr, void *variance_ptr, double epsilon) {
Tensor *input = (Tensor *)input_ptr;
Tensor *gamma = (Tensor *)gamma_ptr;
Tensor *beta = (Tensor *)beta_ptr;
Tensor *mean = (Tensor *)mean_ptr;
Tensor *variance = (Tensor *)variance_ptr;
Tensor *input = (Tensor *) input_ptr;
Tensor *gamma = (Tensor *) gamma_ptr;
Tensor *beta = (Tensor *) beta_ptr;
Tensor *mean = (Tensor *) mean_ptr;
Tensor *variance = (Tensor *) variance_ptr;
deviceToHostCopy(input);
deviceToHostCopy(gamma);
deviceToHostCopy(beta);
deviceToHostCopy(mean);
deviceToHostCopy(variance);
float *__restrict__ host_image = (float *)input->host_data;
float *__restrict__ host_beta = (float *)beta->host_data;
float *__restrict__ host_gamma = (float *)gamma->host_data;
......@@ -1055,7 +1093,10 @@ void *tensorBatchNormCPU(void *input_ptr, void *gamma_ptr, void *beta_ptr,
}
void *tensorReluCPU(void *input_ptr) {
Tensor *input = (Tensor *)input_ptr;
deviceToHostCopy(input);
float *input_data = (float *)input->host_data;
size_t num_elems = input->num_elems;
......@@ -1068,7 +1109,10 @@ void *tensorReluCPU(void *input_ptr) {
}
void *tensorRelu2CPU(void *input_ptr, float min, float max) {
Tensor *input = (Tensor *)input_ptr;
deviceToHostCopy(input);
float *input_data = (float *)input->host_data;
size_t num_elems = input->num_elems;
......
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