f-stack/dpdk/app/test-mldev/test_inference_common.c

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2025-01-10 11:50:43 +00:00
/* SPDX-License-Identifier: BSD-3-Clause
* Copyright (c) 2022 Marvell.
*/
#include <errno.h>
#include <math.h>
#include <stdio.h>
#include <unistd.h>
#include <rte_common.h>
#include <rte_cycles.h>
#include <rte_hash_crc.h>
#include <rte_launch.h>
#include <rte_lcore.h>
#include <rte_malloc.h>
#include <rte_memzone.h>
#include <rte_mldev.h>
#include "ml_common.h"
#include "test_inference_common.h"
#define ML_OPEN_WRITE_GET_ERR(name, buffer, size, err) \
do { \
FILE *fp = fopen(name, "w+"); \
if (fp == NULL) { \
ml_err("Unable to create file: %s, error: %s", name, strerror(errno)); \
err = true; \
} else { \
if (fwrite(buffer, 1, size, fp) != size) { \
ml_err("Error writing output, file: %s, error: %s", name, \
strerror(errno)); \
err = true; \
} \
fclose(fp); \
} \
} while (0)
/* Enqueue inference requests with burst size equal to 1 */
static int
ml_enqueue_single(void *arg)
{
struct test_inference *t = ml_test_priv((struct ml_test *)arg);
struct ml_request *req = NULL;
struct rte_ml_op *op = NULL;
struct ml_core_args *args;
uint64_t model_enq = 0;
uint64_t start_cycle;
uint32_t burst_enq;
uint32_t lcore_id;
uint64_t offset;
uint64_t bufsz;
uint16_t fid;
uint32_t i;
int ret;
lcore_id = rte_lcore_id();
args = &t->args[lcore_id];
args->start_cycles = 0;
model_enq = 0;
if (args->nb_reqs == 0)
return 0;
next_rep:
fid = args->start_fid;
next_model:
ret = rte_mempool_get(t->op_pool, (void **)&op);
if (ret != 0)
goto next_model;
retry_req:
ret = rte_mempool_get(t->model[fid].io_pool, (void **)&req);
if (ret != 0)
goto retry_req;
retry_inp_segs:
ret = rte_mempool_get_bulk(t->buf_seg_pool, (void **)req->inp_buf_segs,
t->model[fid].info.nb_inputs);
if (ret != 0)
goto retry_inp_segs;
retry_out_segs:
ret = rte_mempool_get_bulk(t->buf_seg_pool, (void **)req->out_buf_segs,
t->model[fid].info.nb_outputs);
if (ret != 0)
goto retry_out_segs;
op->model_id = t->model[fid].id;
op->nb_batches = t->model[fid].info.min_batches;
op->mempool = t->op_pool;
op->input = req->inp_buf_segs;
op->output = req->out_buf_segs;
op->user_ptr = req;
if (t->model[fid].info.io_layout == RTE_ML_IO_LAYOUT_PACKED) {
op->input[0]->addr = req->input;
op->input[0]->iova_addr = rte_mem_virt2iova(req->input);
op->input[0]->length = t->model[fid].inp_qsize;
op->input[0]->next = NULL;
op->output[0]->addr = req->output;
op->output[0]->iova_addr = rte_mem_virt2iova(req->output);
op->output[0]->length = t->model[fid].out_qsize;
op->output[0]->next = NULL;
} else {
offset = 0;
for (i = 0; i < t->model[fid].info.nb_inputs; i++) {
bufsz = RTE_ALIGN_CEIL(t->model[fid].info.input_info[i].size,
t->cmn.dev_info.align_size);
op->input[i]->addr = req->input + offset;
op->input[i]->iova_addr = rte_mem_virt2iova(req->input + offset);
op->input[i]->length = bufsz;
op->input[i]->next = NULL;
offset += bufsz;
}
offset = 0;
for (i = 0; i < t->model[fid].info.nb_outputs; i++) {
bufsz = RTE_ALIGN_CEIL(t->model[fid].info.output_info[i].size,
t->cmn.dev_info.align_size);
op->output[i]->addr = req->output + offset;
op->output[i]->iova_addr = rte_mem_virt2iova(req->output + offset);
op->output[i]->length = bufsz;
op->output[i]->next = NULL;
offset += bufsz;
}
}
req->niters++;
req->fid = fid;
enqueue_req:
start_cycle = rte_get_tsc_cycles();
burst_enq = rte_ml_enqueue_burst(t->cmn.opt->dev_id, args->qp_id, &op, 1);
if (burst_enq == 0)
goto enqueue_req;
args->start_cycles += start_cycle;
fid++;
if (likely(fid <= args->end_fid))
goto next_model;
model_enq++;
if (likely(model_enq < args->nb_reqs))
goto next_rep;
return 0;
}
/* Dequeue inference requests with burst size equal to 1 */
static int
ml_dequeue_single(void *arg)
{
struct test_inference *t = ml_test_priv((struct ml_test *)arg);
struct rte_ml_op_error error;
struct rte_ml_op *op = NULL;
struct ml_core_args *args;
struct ml_request *req;
uint64_t total_deq = 0;
uint8_t nb_filelist;
uint32_t burst_deq;
uint64_t end_cycle;
uint32_t lcore_id;
lcore_id = rte_lcore_id();
args = &t->args[lcore_id];
args->end_cycles = 0;
nb_filelist = args->end_fid - args->start_fid + 1;
if (args->nb_reqs == 0)
return 0;
dequeue_req:
burst_deq = rte_ml_dequeue_burst(t->cmn.opt->dev_id, args->qp_id, &op, 1);
end_cycle = rte_get_tsc_cycles();
if (likely(burst_deq == 1)) {
total_deq += burst_deq;
args->end_cycles += end_cycle;
if (unlikely(op->status == RTE_ML_OP_STATUS_ERROR)) {
rte_ml_op_error_get(t->cmn.opt->dev_id, op, &error);
ml_err("error_code = 0x%" PRIx64 ", error_message = %s\n", error.errcode,
error.message);
t->error_count[lcore_id]++;
}
req = (struct ml_request *)op->user_ptr;
rte_mempool_put(t->model[req->fid].io_pool, req);
rte_mempool_put_bulk(t->buf_seg_pool, (void **)op->input,
t->model[req->fid].info.nb_inputs);
rte_mempool_put_bulk(t->buf_seg_pool, (void **)op->output,
t->model[req->fid].info.nb_outputs);
rte_mempool_put(t->op_pool, op);
}
if (likely(total_deq < args->nb_reqs * nb_filelist))
goto dequeue_req;
return 0;
}
/* Enqueue inference requests with burst size greater than 1 */
static int
ml_enqueue_burst(void *arg)
{
struct test_inference *t = ml_test_priv((struct ml_test *)arg);
struct ml_core_args *args;
uint64_t start_cycle;
uint16_t ops_count;
uint64_t model_enq;
uint16_t burst_enq;
uint32_t lcore_id;
uint16_t pending;
uint64_t offset;
uint64_t bufsz;
uint16_t idx;
uint16_t fid;
uint16_t i;
uint16_t j;
int ret;
lcore_id = rte_lcore_id();
args = &t->args[lcore_id];
args->start_cycles = 0;
model_enq = 0;
if (args->nb_reqs == 0)
return 0;
next_rep:
fid = args->start_fid;
next_model:
ops_count = RTE_MIN(t->cmn.opt->burst_size, args->nb_reqs - model_enq);
ret = rte_mempool_get_bulk(t->op_pool, (void **)args->enq_ops, ops_count);
if (ret != 0)
goto next_model;
retry_reqs:
ret = rte_mempool_get_bulk(t->model[fid].io_pool, (void **)args->reqs, ops_count);
if (ret != 0)
goto retry_reqs;
for (i = 0; i < ops_count; i++) {
retry_inp_segs:
ret = rte_mempool_get_bulk(t->buf_seg_pool, (void **)args->reqs[i]->inp_buf_segs,
t->model[fid].info.nb_inputs);
if (ret != 0)
goto retry_inp_segs;
retry_out_segs:
ret = rte_mempool_get_bulk(t->buf_seg_pool, (void **)args->reqs[i]->out_buf_segs,
t->model[fid].info.nb_outputs);
if (ret != 0)
goto retry_out_segs;
args->enq_ops[i]->model_id = t->model[fid].id;
args->enq_ops[i]->nb_batches = t->model[fid].info.min_batches;
args->enq_ops[i]->mempool = t->op_pool;
args->enq_ops[i]->input = args->reqs[i]->inp_buf_segs;
args->enq_ops[i]->output = args->reqs[i]->out_buf_segs;
args->enq_ops[i]->user_ptr = args->reqs[i];
if (t->model[fid].info.io_layout == RTE_ML_IO_LAYOUT_PACKED) {
args->enq_ops[i]->input[0]->addr = args->reqs[i]->input;
args->enq_ops[i]->input[0]->iova_addr =
rte_mem_virt2iova(args->reqs[i]->input);
args->enq_ops[i]->input[0]->length = t->model[fid].inp_qsize;
args->enq_ops[i]->input[0]->next = NULL;
args->enq_ops[i]->output[0]->addr = args->reqs[i]->output;
args->enq_ops[i]->output[0]->iova_addr =
rte_mem_virt2iova(args->reqs[i]->output);
args->enq_ops[i]->output[0]->length = t->model[fid].out_qsize;
args->enq_ops[i]->output[0]->next = NULL;
} else {
offset = 0;
for (j = 0; j < t->model[fid].info.nb_inputs; j++) {
bufsz = RTE_ALIGN_CEIL(t->model[fid].info.input_info[i].size,
t->cmn.dev_info.align_size);
args->enq_ops[i]->input[j]->addr = args->reqs[i]->input + offset;
args->enq_ops[i]->input[j]->iova_addr =
rte_mem_virt2iova(args->reqs[i]->input + offset);
args->enq_ops[i]->input[j]->length = t->model[fid].inp_qsize;
args->enq_ops[i]->input[j]->next = NULL;
offset += bufsz;
}
offset = 0;
for (j = 0; j < t->model[fid].info.nb_outputs; j++) {
bufsz = RTE_ALIGN_CEIL(t->model[fid].info.output_info[i].size,
t->cmn.dev_info.align_size);
args->enq_ops[i]->output[j]->addr = args->reqs[i]->output + offset;
args->enq_ops[i]->output[j]->iova_addr =
rte_mem_virt2iova(args->reqs[i]->output + offset);
args->enq_ops[i]->output[j]->length = t->model[fid].out_qsize;
args->enq_ops[i]->output[j]->next = NULL;
offset += bufsz;
}
}
args->reqs[i]->niters++;
args->reqs[i]->fid = fid;
}
idx = 0;
pending = ops_count;
enqueue_reqs:
start_cycle = rte_get_tsc_cycles();
burst_enq =
rte_ml_enqueue_burst(t->cmn.opt->dev_id, args->qp_id, &args->enq_ops[idx], pending);
args->start_cycles += burst_enq * start_cycle;
pending = pending - burst_enq;
if (pending > 0) {
idx = idx + burst_enq;
goto enqueue_reqs;
}
fid++;
if (fid <= args->end_fid)
goto next_model;
model_enq = model_enq + ops_count;
if (model_enq < args->nb_reqs)
goto next_rep;
return 0;
}
/* Dequeue inference requests with burst size greater than 1 */
static int
ml_dequeue_burst(void *arg)
{
struct test_inference *t = ml_test_priv((struct ml_test *)arg);
struct rte_ml_op_error error;
struct ml_core_args *args;
struct ml_request *req;
uint64_t total_deq = 0;
uint16_t burst_deq = 0;
uint8_t nb_filelist;
uint64_t end_cycle;
uint32_t lcore_id;
uint32_t i;
lcore_id = rte_lcore_id();
args = &t->args[lcore_id];
args->end_cycles = 0;
nb_filelist = args->end_fid - args->start_fid + 1;
if (args->nb_reqs == 0)
return 0;
dequeue_burst:
burst_deq = rte_ml_dequeue_burst(t->cmn.opt->dev_id, args->qp_id, args->deq_ops,
t->cmn.opt->burst_size);
end_cycle = rte_get_tsc_cycles();
if (likely(burst_deq > 0)) {
total_deq += burst_deq;
args->end_cycles += burst_deq * end_cycle;
for (i = 0; i < burst_deq; i++) {
if (unlikely(args->deq_ops[i]->status == RTE_ML_OP_STATUS_ERROR)) {
rte_ml_op_error_get(t->cmn.opt->dev_id, args->deq_ops[i], &error);
ml_err("error_code = 0x%" PRIx64 ", error_message = %s\n",
error.errcode, error.message);
t->error_count[lcore_id]++;
}
req = (struct ml_request *)args->deq_ops[i]->user_ptr;
if (req != NULL) {
rte_mempool_put(t->model[req->fid].io_pool, req);
rte_mempool_put_bulk(t->buf_seg_pool,
(void **)args->deq_ops[i]->input,
t->model[req->fid].info.nb_inputs);
rte_mempool_put_bulk(t->buf_seg_pool,
(void **)args->deq_ops[i]->output,
t->model[req->fid].info.nb_outputs);
}
}
rte_mempool_put_bulk(t->op_pool, (void *)args->deq_ops, burst_deq);
}
if (total_deq < args->nb_reqs * nb_filelist)
goto dequeue_burst;
return 0;
}
bool
test_inference_cap_check(struct ml_options *opt)
{
struct rte_ml_dev_info dev_info;
if (!ml_test_cap_check(opt))
return false;
rte_ml_dev_info_get(opt->dev_id, &dev_info);
if (opt->queue_pairs > dev_info.max_queue_pairs) {
ml_err("Insufficient capabilities: queue_pairs = %u > (max_queue_pairs = %u)",
opt->queue_pairs, dev_info.max_queue_pairs);
return false;
}
if (opt->queue_size > dev_info.max_desc) {
ml_err("Insufficient capabilities: queue_size = %u > (max_desc = %u)",
opt->queue_size, dev_info.max_desc);
return false;
}
if (opt->nb_filelist > dev_info.max_models) {
ml_err("Insufficient capabilities: Filelist count exceeded device limit, count = %u > (max limit = %u)",
opt->nb_filelist, dev_info.max_models);
return false;
}
if (dev_info.max_io < ML_TEST_MAX_IO_SIZE) {
ml_err("Insufficient capabilities: Max I/O, count = %u > (max limit = %u)",
ML_TEST_MAX_IO_SIZE, dev_info.max_io);
return false;
}
return true;
}
int
test_inference_opt_check(struct ml_options *opt)
{
uint32_t i;
int ret;
/* check common opts */
ret = ml_test_opt_check(opt);
if (ret != 0)
return ret;
/* check for at least one filelist */
if (opt->nb_filelist == 0) {
ml_err("Filelist empty, need at least one filelist to run the test\n");
return -EINVAL;
}
/* check file availability */
for (i = 0; i < opt->nb_filelist; i++) {
if (access(opt->filelist[i].model, F_OK) == -1) {
ml_err("Model file not accessible: id = %u, file = %s", i,
opt->filelist[i].model);
return -ENOENT;
}
if (access(opt->filelist[i].input, F_OK) == -1) {
ml_err("Input file not accessible: id = %u, file = %s", i,
opt->filelist[i].input);
return -ENOENT;
}
}
if (opt->repetitions == 0) {
ml_err("Invalid option, repetitions = %" PRIu64 "\n", opt->repetitions);
return -EINVAL;
}
if (opt->burst_size == 0) {
ml_err("Invalid option, burst_size = %u\n", opt->burst_size);
return -EINVAL;
}
if (opt->burst_size > ML_TEST_MAX_POOL_SIZE) {
ml_err("Invalid option, burst_size = %u (> max supported = %d)\n", opt->burst_size,
ML_TEST_MAX_POOL_SIZE);
return -EINVAL;
}
if (opt->queue_pairs == 0) {
ml_err("Invalid option, queue_pairs = %u\n", opt->queue_pairs);
return -EINVAL;
}
if (opt->queue_size == 0) {
ml_err("Invalid option, queue_size = %u\n", opt->queue_size);
return -EINVAL;
}
/* check number of available lcores. */
if (rte_lcore_count() < (uint32_t)(opt->queue_pairs * 2 + 1)) {
ml_err("Insufficient lcores = %u\n", rte_lcore_count());
ml_err("Minimum lcores required to create %u queue-pairs = %u\n", opt->queue_pairs,
(opt->queue_pairs * 2 + 1));
return -EINVAL;
}
return 0;
}
void
test_inference_opt_dump(struct ml_options *opt)
{
uint32_t i;
/* dump common opts */
ml_test_opt_dump(opt);
/* dump test opts */
ml_dump("repetitions", "%" PRIu64, opt->repetitions);
ml_dump("burst_size", "%u", opt->burst_size);
ml_dump("queue_pairs", "%u", opt->queue_pairs);
ml_dump("queue_size", "%u", opt->queue_size);
ml_dump("tolerance", "%-7.3f", opt->tolerance);
ml_dump("stats", "%s", (opt->stats ? "true" : "false"));
ml_dump_begin("filelist");
for (i = 0; i < opt->nb_filelist; i++) {
ml_dump_list("model", i, opt->filelist[i].model);
ml_dump_list("input", i, opt->filelist[i].input);
ml_dump_list("output", i, opt->filelist[i].output);
if (strcmp(opt->filelist[i].reference, "\0") != 0)
ml_dump_list("reference", i, opt->filelist[i].reference);
}
ml_dump_end;
}
int
test_inference_setup(struct ml_test *test, struct ml_options *opt)
{
struct test_inference *t;
void *test_inference;
uint32_t lcore_id;
int ret = 0;
uint32_t i;
test_inference = rte_zmalloc_socket(test->name, sizeof(struct test_inference),
RTE_CACHE_LINE_SIZE, opt->socket_id);
if (test_inference == NULL) {
ml_err("failed to allocate memory for test_model");
ret = -ENOMEM;
goto error;
}
test->test_priv = test_inference;
t = ml_test_priv(test);
t->nb_used = 0;
t->nb_valid = 0;
t->cmn.result = ML_TEST_FAILED;
t->cmn.opt = opt;
memset(t->error_count, 0, RTE_MAX_LCORE * sizeof(uint64_t));
/* get device info */
ret = rte_ml_dev_info_get(opt->dev_id, &t->cmn.dev_info);
if (ret < 0) {
ml_err("failed to get device info");
goto error;
}
if (opt->burst_size == 1) {
t->enqueue = ml_enqueue_single;
t->dequeue = ml_dequeue_single;
} else {
t->enqueue = ml_enqueue_burst;
t->dequeue = ml_dequeue_burst;
}
/* set model initial state */
for (i = 0; i < opt->nb_filelist; i++)
t->model[i].state = MODEL_INITIAL;
for (lcore_id = 0; lcore_id < RTE_MAX_LCORE; lcore_id++) {
t->args[lcore_id].enq_ops = rte_zmalloc_socket(
"ml_test_enq_ops", opt->burst_size * sizeof(struct rte_ml_op *),
RTE_CACHE_LINE_SIZE, opt->socket_id);
t->args[lcore_id].deq_ops = rte_zmalloc_socket(
"ml_test_deq_ops", opt->burst_size * sizeof(struct rte_ml_op *),
RTE_CACHE_LINE_SIZE, opt->socket_id);
t->args[lcore_id].reqs = rte_zmalloc_socket(
"ml_test_requests", opt->burst_size * sizeof(struct ml_request *),
RTE_CACHE_LINE_SIZE, opt->socket_id);
}
for (i = 0; i < RTE_MAX_LCORE; i++) {
t->args[i].start_cycles = 0;
t->args[i].end_cycles = 0;
}
return 0;
error:
rte_free(test_inference);
return ret;
}
void
test_inference_destroy(struct ml_test *test, struct ml_options *opt)
{
struct test_inference *t;
uint32_t lcore_id;
RTE_SET_USED(opt);
t = ml_test_priv(test);
for (lcore_id = 0; lcore_id < RTE_MAX_LCORE; lcore_id++) {
rte_free(t->args[lcore_id].enq_ops);
rte_free(t->args[lcore_id].deq_ops);
rte_free(t->args[lcore_id].reqs);
}
rte_free(t);
}
int
ml_inference_mldev_setup(struct ml_test *test, struct ml_options *opt)
{
struct rte_ml_dev_qp_conf qp_conf;
struct test_inference *t;
uint16_t qp_id;
int ret;
t = ml_test_priv(test);
RTE_SET_USED(t);
ret = ml_test_device_configure(test, opt);
if (ret != 0)
return ret;
/* setup queue pairs */
qp_conf.nb_desc = opt->queue_size;
qp_conf.cb = NULL;
for (qp_id = 0; qp_id < opt->queue_pairs; qp_id++) {
qp_conf.nb_desc = opt->queue_size;
qp_conf.cb = NULL;
ret = rte_ml_dev_queue_pair_setup(opt->dev_id, qp_id, &qp_conf, opt->socket_id);
if (ret != 0) {
ml_err("Failed to setup ml device queue-pair, dev_id = %d, qp_id = %u\n",
opt->dev_id, qp_id);
return ret;
}
}
ret = ml_test_device_start(test, opt);
if (ret != 0)
goto error;
return 0;
error:
ml_test_device_close(test, opt);
return ret;
}
int
ml_inference_mldev_destroy(struct ml_test *test, struct ml_options *opt)
{
int ret;
ret = ml_test_device_stop(test, opt);
if (ret != 0)
goto error;
ret = ml_test_device_close(test, opt);
if (ret != 0)
return ret;
return 0;
error:
ml_test_device_close(test, opt);
return ret;
}
/* Callback for IO pool create. This function would compute the fields of ml_request
* structure and prepare the quantized input data.
*/
static void
ml_request_initialize(struct rte_mempool *mp, void *opaque, void *obj, unsigned int obj_idx)
{
struct test_inference *t = ml_test_priv((struct ml_test *)opaque);
struct ml_request *req = (struct ml_request *)obj;
struct rte_ml_buff_seg dbuff_seg[ML_TEST_MAX_IO_SIZE];
struct rte_ml_buff_seg qbuff_seg[ML_TEST_MAX_IO_SIZE];
struct rte_ml_buff_seg *q_segs[ML_TEST_MAX_IO_SIZE];
struct rte_ml_buff_seg *d_segs[ML_TEST_MAX_IO_SIZE];
uint64_t offset;
uint64_t bufsz;
uint32_t i;
RTE_SET_USED(mp);
RTE_SET_USED(obj_idx);
req->input = (uint8_t *)obj +
RTE_ALIGN_CEIL(sizeof(struct ml_request), t->cmn.dev_info.align_size);
req->output =
req->input + RTE_ALIGN_CEIL(t->model[t->fid].inp_qsize, t->cmn.dev_info.align_size);
req->niters = 0;
if (t->model[t->fid].info.io_layout == RTE_ML_IO_LAYOUT_PACKED) {
dbuff_seg[0].addr = t->model[t->fid].input;
dbuff_seg[0].iova_addr = rte_mem_virt2iova(t->model[t->fid].input);
dbuff_seg[0].length = t->model[t->fid].inp_dsize;
dbuff_seg[0].next = NULL;
d_segs[0] = &dbuff_seg[0];
qbuff_seg[0].addr = req->input;
qbuff_seg[0].iova_addr = rte_mem_virt2iova(req->input);
qbuff_seg[0].length = t->model[t->fid].inp_qsize;
qbuff_seg[0].next = NULL;
q_segs[0] = &qbuff_seg[0];
} else {
offset = 0;
for (i = 0; i < t->model[t->fid].info.nb_inputs; i++) {
bufsz = t->model[t->fid].info.input_info[i].nb_elements * sizeof(float);
dbuff_seg[i].addr = t->model[t->fid].input + offset;
dbuff_seg[i].iova_addr = rte_mem_virt2iova(t->model[t->fid].input + offset);
dbuff_seg[i].length = bufsz;
dbuff_seg[i].next = NULL;
d_segs[i] = &dbuff_seg[i];
offset += bufsz;
}
offset = 0;
for (i = 0; i < t->model[t->fid].info.nb_inputs; i++) {
bufsz = RTE_ALIGN_CEIL(t->model[t->fid].info.input_info[i].size,
t->cmn.dev_info.align_size);
qbuff_seg[i].addr = req->input + offset;
qbuff_seg[i].iova_addr = rte_mem_virt2iova(req->input + offset);
qbuff_seg[i].length = bufsz;
qbuff_seg[i].next = NULL;
q_segs[i] = &qbuff_seg[i];
offset += bufsz;
}
}
/* quantize data */
rte_ml_io_quantize(t->cmn.opt->dev_id, t->model[t->fid].id, d_segs, q_segs);
}
int
ml_inference_iomem_setup(struct ml_test *test, struct ml_options *opt, uint16_t fid)
{
struct test_inference *t = ml_test_priv(test);
char mz_name[RTE_MEMZONE_NAMESIZE];
char mp_name[RTE_MEMPOOL_NAMESIZE];
const struct rte_memzone *mz;
uint64_t nb_buffers;
char *buffer = NULL;
uint32_t buff_size;
uint32_t mz_size;
size_t fsize;
uint32_t i;
int ret;
/* get input buffer size */
t->model[fid].inp_qsize = 0;
for (i = 0; i < t->model[fid].info.nb_inputs; i++) {
if (t->model[fid].info.io_layout == RTE_ML_IO_LAYOUT_PACKED)
t->model[fid].inp_qsize += t->model[fid].info.input_info[i].size;
else
t->model[fid].inp_qsize += RTE_ALIGN_CEIL(
t->model[fid].info.input_info[i].size, t->cmn.dev_info.align_size);
}
/* get output buffer size */
t->model[fid].out_qsize = 0;
for (i = 0; i < t->model[fid].info.nb_outputs; i++) {
if (t->model[fid].info.io_layout == RTE_ML_IO_LAYOUT_PACKED)
t->model[fid].out_qsize += t->model[fid].info.output_info[i].size;
else
t->model[fid].out_qsize += RTE_ALIGN_CEIL(
t->model[fid].info.output_info[i].size, t->cmn.dev_info.align_size);
}
t->model[fid].inp_dsize = 0;
for (i = 0; i < t->model[fid].info.nb_inputs; i++) {
if (opt->quantized_io)
t->model[fid].inp_dsize += t->model[fid].info.input_info[i].size;
else
t->model[fid].inp_dsize +=
t->model[fid].info.input_info[i].nb_elements * sizeof(float);
}
t->model[fid].out_dsize = 0;
for (i = 0; i < t->model[fid].info.nb_outputs; i++) {
if (opt->quantized_io)
t->model[fid].out_dsize += t->model[fid].info.output_info[i].size;
else
t->model[fid].out_dsize +=
t->model[fid].info.output_info[i].nb_elements * sizeof(float);
}
/* allocate buffer for user data */
mz_size = t->model[fid].inp_dsize + t->model[fid].out_dsize;
if (strcmp(opt->filelist[fid].reference, "\0") != 0)
mz_size += t->model[fid].out_dsize;
sprintf(mz_name, "ml_user_data_%d", fid);
mz = rte_memzone_reserve(mz_name, mz_size, opt->socket_id, 0);
if (mz == NULL) {
ml_err("Memzone allocation failed for ml_user_data\n");
ret = -ENOMEM;
goto error;
}
t->model[fid].input = mz->addr;
t->model[fid].output = t->model[fid].input + t->model[fid].inp_dsize;
if (strcmp(opt->filelist[fid].reference, "\0") != 0)
t->model[fid].reference = t->model[fid].output + t->model[fid].out_dsize;
else
t->model[fid].reference = NULL;
/* load input file */
ret = ml_read_file(opt->filelist[fid].input, &fsize, &buffer);
if (ret != 0)
goto error;
if (fsize == t->model[fid].inp_dsize) {
rte_memcpy(t->model[fid].input, buffer, fsize);
free(buffer);
} else {
ml_err("Invalid input file, size = %zu (expected size = %" PRIu64 ")\n", fsize,
t->model[fid].inp_dsize);
ret = -EINVAL;
free(buffer);
goto error;
}
/* load reference file */
buffer = NULL;
if (t->model[fid].reference != NULL) {
ret = ml_read_file(opt->filelist[fid].reference, &fsize, &buffer);
if (ret != 0)
goto error;
if (fsize == t->model[fid].out_dsize) {
rte_memcpy(t->model[fid].reference, buffer, fsize);
free(buffer);
} else {
ml_err("Invalid reference file, size = %zu (expected size = %" PRIu64 ")\n",
fsize, t->model[fid].out_dsize);
ret = -EINVAL;
free(buffer);
goto error;
}
}
/* create mempool for quantized input and output buffers. ml_request_initialize is
* used as a callback for object creation.
*/
buff_size = RTE_ALIGN_CEIL(sizeof(struct ml_request), t->cmn.dev_info.align_size) +
RTE_ALIGN_CEIL(t->model[fid].inp_qsize, t->cmn.dev_info.align_size) +
RTE_ALIGN_CEIL(t->model[fid].out_qsize, t->cmn.dev_info.align_size);
nb_buffers = RTE_MIN((uint64_t)ML_TEST_MAX_POOL_SIZE, opt->repetitions);
t->fid = fid;
sprintf(mp_name, "ml_io_pool_%d", fid);
t->model[fid].io_pool = rte_mempool_create(mp_name, nb_buffers, buff_size, 0, 0, NULL, NULL,
ml_request_initialize, test, opt->socket_id, 0);
if (t->model[fid].io_pool == NULL) {
ml_err("Failed to create io pool : %s\n", "ml_io_pool");
ret = -ENOMEM;
goto error;
}
return 0;
error:
if (mz != NULL)
rte_memzone_free(mz);
if (t->model[fid].io_pool != NULL) {
rte_mempool_free(t->model[fid].io_pool);
t->model[fid].io_pool = NULL;
}
return ret;
}
void
ml_inference_iomem_destroy(struct ml_test *test, struct ml_options *opt, uint16_t fid)
{
char mz_name[RTE_MEMZONE_NAMESIZE];
char mp_name[RTE_MEMPOOL_NAMESIZE];
const struct rte_memzone *mz;
struct rte_mempool *mp;
RTE_SET_USED(test);
RTE_SET_USED(opt);
/* release user data memzone */
sprintf(mz_name, "ml_user_data_%d", fid);
mz = rte_memzone_lookup(mz_name);
if (mz != NULL)
rte_memzone_free(mz);
/* destroy io pool */
sprintf(mp_name, "ml_io_pool_%d", fid);
mp = rte_mempool_lookup(mp_name);
rte_mempool_free(mp);
}
int
ml_inference_mem_setup(struct ml_test *test, struct ml_options *opt)
{
struct test_inference *t = ml_test_priv(test);
/* create op pool */
t->op_pool = rte_ml_op_pool_create("ml_test_op_pool", ML_TEST_MAX_POOL_SIZE, 0, 0,
opt->socket_id);
if (t->op_pool == NULL) {
ml_err("Failed to create op pool : %s\n", "ml_op_pool");
return -ENOMEM;
}
/* create buf_segs pool of with element of uint8_t. external buffers are attached to the
* buf_segs while queuing inference requests.
*/
t->buf_seg_pool = rte_mempool_create("ml_test_mbuf_pool", ML_TEST_MAX_POOL_SIZE * 2,
sizeof(struct rte_ml_buff_seg), 0, 0, NULL, NULL, NULL,
NULL, opt->socket_id, 0);
if (t->buf_seg_pool == NULL) {
ml_err("Failed to create buf_segs pool : %s\n", "ml_test_mbuf_pool");
rte_ml_op_pool_free(t->op_pool);
return -ENOMEM;
}
return 0;
}
void
ml_inference_mem_destroy(struct ml_test *test, struct ml_options *opt)
{
struct test_inference *t = ml_test_priv(test);
RTE_SET_USED(opt);
/* release op pool */
rte_mempool_free(t->op_pool);
/* release buf_segs pool */
rte_mempool_free(t->buf_seg_pool);
}
static bool
ml_inference_validation(struct ml_test *test, struct ml_request *req)
{
struct test_inference *t = ml_test_priv((struct ml_test *)test);
struct ml_model *model;
float *reference;
float *output;
float deviation;
bool match;
uint32_t i;
uint32_t j;
model = &t->model[req->fid];
/* compare crc when tolerance is 0 */
if (t->cmn.opt->tolerance == 0.0) {
match = (rte_hash_crc(model->output, model->out_dsize, 0) ==
rte_hash_crc(model->reference, model->out_dsize, 0));
} else {
output = (float *)model->output;
reference = (float *)model->reference;
i = 0;
next_output:
j = 0;
next_element:
match = false;
if ((*reference == 0) && (*output == 0))
deviation = 0;
else
deviation = 100 * fabs(*output - *reference) / fabs(*reference);
if (deviation <= t->cmn.opt->tolerance)
match = true;
else
ml_err("id = %d, element = %d, output = %f, reference = %f, deviation = %f %%\n",
i, j, *output, *reference, deviation);
output++;
reference++;
if (!match)
goto done;
j++;
if (j < model->info.output_info[i].nb_elements)
goto next_element;
i++;
if (i < model->info.nb_outputs)
goto next_output;
}
done:
return match;
}
/* Callback for mempool object iteration. This call would dequantize output data. */
static void
ml_request_finish(struct rte_mempool *mp, void *opaque, void *obj, unsigned int obj_idx)
{
struct test_inference *t = ml_test_priv((struct ml_test *)opaque);
struct ml_request *req = (struct ml_request *)obj;
struct ml_model *model = &t->model[req->fid];
bool error = false;
char *dump_path;
struct rte_ml_buff_seg qbuff_seg[ML_TEST_MAX_IO_SIZE];
struct rte_ml_buff_seg dbuff_seg[ML_TEST_MAX_IO_SIZE];
struct rte_ml_buff_seg *q_segs[ML_TEST_MAX_IO_SIZE];
struct rte_ml_buff_seg *d_segs[ML_TEST_MAX_IO_SIZE];
uint64_t offset;
uint64_t bufsz;
uint32_t i;
RTE_SET_USED(mp);
if (req->niters == 0)
return;
t->nb_used++;
if (t->model[req->fid].info.io_layout == RTE_ML_IO_LAYOUT_PACKED) {
qbuff_seg[0].addr = req->output;
qbuff_seg[0].iova_addr = rte_mem_virt2iova(req->output);
qbuff_seg[0].length = t->model[req->fid].out_qsize;
qbuff_seg[0].next = NULL;
q_segs[0] = &qbuff_seg[0];
dbuff_seg[0].addr = model->output;
dbuff_seg[0].iova_addr = rte_mem_virt2iova(model->output);
dbuff_seg[0].length = t->model[req->fid].out_dsize;
dbuff_seg[0].next = NULL;
d_segs[0] = &dbuff_seg[0];
} else {
offset = 0;
for (i = 0; i < t->model[req->fid].info.nb_outputs; i++) {
bufsz = RTE_ALIGN_CEIL(t->model[req->fid].info.output_info[i].size,
t->cmn.dev_info.align_size);
qbuff_seg[i].addr = req->output + offset;
qbuff_seg[i].iova_addr = rte_mem_virt2iova(req->output + offset);
qbuff_seg[i].length = bufsz;
qbuff_seg[i].next = NULL;
q_segs[i] = &qbuff_seg[i];
offset += bufsz;
}
offset = 0;
for (i = 0; i < t->model[req->fid].info.nb_outputs; i++) {
bufsz = t->model[req->fid].info.output_info[i].nb_elements * sizeof(float);
dbuff_seg[i].addr = model->output + offset;
dbuff_seg[i].iova_addr = rte_mem_virt2iova(model->output + offset);
dbuff_seg[i].length = bufsz;
dbuff_seg[i].next = NULL;
d_segs[i] = &dbuff_seg[i];
offset += bufsz;
}
}
rte_ml_io_dequantize(t->cmn.opt->dev_id, model->id, q_segs, d_segs);
if (model->reference == NULL)
goto dump_output_pass;
if (!ml_inference_validation(opaque, req))
goto dump_output_fail;
else
goto dump_output_pass;
dump_output_pass:
if (obj_idx == 0) {
/* write quantized output */
if (asprintf(&dump_path, "%s.q", t->cmn.opt->filelist[req->fid].output) == -1)
return;
ML_OPEN_WRITE_GET_ERR(dump_path, req->output, model->out_qsize, error);
free(dump_path);
if (error)
return;
/* write dequantized output */
if (asprintf(&dump_path, "%s", t->cmn.opt->filelist[req->fid].output) == -1)
return;
ML_OPEN_WRITE_GET_ERR(dump_path, model->output, model->out_dsize, error);
free(dump_path);
if (error)
return;
}
t->nb_valid++;
return;
dump_output_fail:
if (t->cmn.opt->debug) {
/* dump quantized output buffer */
if (asprintf(&dump_path, "%s.q.%u", t->cmn.opt->filelist[req->fid].output,
obj_idx) == -1)
return;
ML_OPEN_WRITE_GET_ERR(dump_path, req->output, model->out_qsize, error);
free(dump_path);
if (error)
return;
/* dump dequantized output buffer */
if (asprintf(&dump_path, "%s.%u", t->cmn.opt->filelist[req->fid].output, obj_idx) ==
-1)
return;
ML_OPEN_WRITE_GET_ERR(dump_path, model->output, model->out_dsize, error);
free(dump_path);
if (error)
return;
}
}
int
ml_inference_result(struct ml_test *test, struct ml_options *opt, uint16_t fid)
{
struct test_inference *t = ml_test_priv(test);
uint64_t error_count = 0;
uint32_t i;
RTE_SET_USED(opt);
/* check for errors */
for (i = 0; i < RTE_MAX_LCORE; i++)
error_count += t->error_count[i];
rte_mempool_obj_iter(t->model[fid].io_pool, ml_request_finish, test);
if ((t->nb_used == t->nb_valid) && (error_count == 0))
t->cmn.result = ML_TEST_SUCCESS;
else
t->cmn.result = ML_TEST_FAILED;
return t->cmn.result;
}
int
ml_inference_launch_cores(struct ml_test *test, struct ml_options *opt, uint16_t start_fid,
uint16_t end_fid)
{
struct test_inference *t = ml_test_priv(test);
uint32_t lcore_id;
uint32_t nb_reqs;
uint32_t id = 0;
uint32_t qp_id;
nb_reqs = opt->repetitions / opt->queue_pairs;
RTE_LCORE_FOREACH_WORKER(lcore_id)
{
if (id >= opt->queue_pairs * 2)
break;
qp_id = id / 2;
t->args[lcore_id].qp_id = qp_id;
t->args[lcore_id].nb_reqs = nb_reqs;
if (qp_id == 0)
t->args[lcore_id].nb_reqs += opt->repetitions - nb_reqs * opt->queue_pairs;
if (t->args[lcore_id].nb_reqs == 0) {
id++;
break;
}
t->args[lcore_id].start_fid = start_fid;
t->args[lcore_id].end_fid = end_fid;
if (id % 2 == 0)
rte_eal_remote_launch(t->enqueue, test, lcore_id);
else
rte_eal_remote_launch(t->dequeue, test, lcore_id);
id++;
}
return 0;
}