blob: b4f7b34a6ad61eb2b1b0222023beca4c8de45043 [file] [log] [blame]
// Mobilenet_v1_0.25_224 quant model
// MlModel struct initialization to include model I/O info.
// Bytecode loading, input/output processes.
#include <springbok.h>
#include "iree/base/api.h"
#include "iree/hal/api.h"
#include "mobilenet_v1.h"
#include "samples/util/util.h"
// Compiled module embedded here to avoid file IO:
#include "samples/quant_model/mobilenet_quant_input_c.h"
#if !defined(BUILD_EMITC)
#include "samples/quant_model/mobilenet_v1_bytecode_module_static.h"
#include "samples/quant_model/mobilenet_v1_bytecode_module_static_c.h"
#else
#include "samples/quant_model/mobilenet_v1_c_module_static_c.h"
#include "samples/quant_model/mobilenet_v1_c_module_static_emitc.h"
#endif
const MlModel kModel = {
.num_input = 1,
.num_input_dim = {4},
.input_shape = {{1, 224, 224, 3}},
.input_length = {224 * 224 * 3},
.input_size_bytes = {sizeof(uint8_t)},
.num_output = 1,
.output_length = {1001},
.output_size_bytes = sizeof(uint8_t),
.hal_element_type = IREE_HAL_ELEMENT_TYPE_UINT_8,
.entry_func = "module.main",
.model_name = "mobilenet_v1_0.25_224_quant",
};
MobilenetV1Output score;
iree_status_t create_module(iree_vm_module_t **module) {
#if !defined(BUILD_EMITC)
const struct iree_file_toc_t *module_file_toc =
samples_quant_model_mobilenet_v1_bytecode_module_static_create();
return iree_vm_bytecode_module_create(
iree_make_const_byte_span(module_file_toc->data, module_file_toc->size),
iree_allocator_null(), iree_allocator_system(), module);
#else
return module_create(iree_allocator_system(), module);
#endif
}
iree_hal_executable_library_query_fn_t library_query(void) {
#if !defined(BUILD_EMITC)
return &mobilenet_v1_bytecode_module_static_linked_llvm_library_query;
#else
return &mobilenet_v1_c_module_static_linked_llvm_library_query;
#endif
}
iree_status_t load_input_data(const MlModel *model, void **buffer,
iree_const_byte_span_t **byte_span) {
byte_span[0] = malloc(sizeof(iree_const_byte_span_t));
*byte_span[0] = iree_make_const_byte_span(
mobilenet_quant_input,
model->input_size_bytes[0] * model->input_length[0]);
return iree_ok_status();
}
iree_status_t process_output(const MlModel *model,
iree_hal_buffer_mapping_t *buffers,
MlOutput *output) {
iree_status_t result = iree_ok_status();
// find the label index with best prediction
int best_out = 0;
int best_idx = -1;
for (int i = 0; i < model->output_length[0]; ++i) {
uint8_t out = ((uint8_t *)buffers[0].contents.data)[i];
if (out > best_out) {
best_out = out;
best_idx = i;
}
}
score.best_out = best_out;
score.best_idx = best_idx;
LOG_INFO("Image prediction result is: id: %d", best_idx + 1);
output->result = &score;
output->len = sizeof(score);
return result;
}