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Refactor rknn code (#2079)

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This commit is contained in:
Fangjun Kuang
2025-04-01 16:54:53 +08:00
committed by GitHub
parent 8e51a97550
commit a11e359c11
6 changed files with 218 additions and 451 deletions
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301
sherpa-onnx/csrc/rknn/online-zipformer-transducer-model-rknn.cc
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@@ -62,65 +62,31 @@ class OnlineZipformerTransducerModelRknn::Impl {
InitJoiner(buf.data(), buf.size());
}
// Now select which core to run for RK3588
int32_t ret_encoder = RKNN_SUCC;
int32_t ret_decoder = RKNN_SUCC;
int32_t ret_joiner = RKNN_SUCC;
switch (config_.num_threads) {
case 1:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_AUTO);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_AUTO);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_AUTO);
break;
case 0:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_0);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_0);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_0);
break;
case -1:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_1);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_1);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_1);
break;
case -2:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_2);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_2);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_2);
break;
case -3:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_0_1);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_0_1);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_0_1);
break;
case -4:
ret_encoder = rknn_set_core_mask(encoder_ctx_, RKNN_NPU_CORE_0_1_2);
ret_decoder = rknn_set_core_mask(decoder_ctx_, RKNN_NPU_CORE_0_1_2);
ret_joiner = rknn_set_core_mask(joiner_ctx_, RKNN_NPU_CORE_0_1_2);
break;
default:
SHERPA_ONNX_LOGE(
"Valid num_threads for rk npu is 1 (auto), 0 (core 0), -1 (core "
"1), -2 (core 2), -3 (core 0_1), -4 (core 0_1_2). Given: %d",
config_.num_threads);
break;
}
if (ret_encoder != RKNN_SUCC) {
SHERPA_ONNX_LOGE(
"Failed to select npu core to run encoder (You can ignore it if you "
"are not using RK3588.");
SetCoreMask(encoder_ctx_, config_.num_threads);
SetCoreMask(decoder_ctx_, config_.num_threads);
SetCoreMask(joiner_ctx_, config_.num_threads);
}
template <typename Manager>
Impl(Manager *mgr, const OnlineModelConfig &config) : config_(config) {
{
auto buf = ReadFile(mgr, config.transducer.encoder);
InitEncoder(buf.data(), buf.size());
}
if (ret_decoder != RKNN_SUCC) {
SHERPA_ONNX_LOGE(
"Failed to select npu core to run decoder (You can ignore it if you "
"are not using RK3588.");
{
auto buf = ReadFile(mgr, config.transducer.decoder);
InitDecoder(buf.data(), buf.size());
}
if (ret_decoder != RKNN_SUCC) {
SHERPA_ONNX_LOGE(
"Failed to select npu core to run joiner (You can ignore it if you "
"are not using RK3588.");
{
auto buf = ReadFile(mgr, config.transducer.joiner);
InitJoiner(buf.data(), buf.size());
}
SetCoreMask(encoder_ctx_, config_.num_threads);
SetCoreMask(decoder_ctx_, config_.num_threads);
SetCoreMask(joiner_ctx_, config_.num_threads);
}
// TODO(fangjun): Support Android
@@ -325,93 +291,15 @@ class OnlineZipformerTransducerModelRknn::Impl {
private:
void InitEncoder(void *model_data, size_t model_data_length) {
auto ret =
rknn_init(&encoder_ctx_, model_data, model_data_length, 0, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to init encoder '%s'",
config_.transducer.encoder.c_str());
InitContext(model_data, model_data_length, config_.debug, &encoder_ctx_);
if (config_.debug) {
rknn_sdk_version v;
ret = rknn_query(encoder_ctx_, RKNN_QUERY_SDK_VERSION, &v, sizeof(v));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get rknn sdk version");
InitInputOutputAttrs(encoder_ctx_, config_.debug, &encoder_input_attrs_,
&encoder_output_attrs_);
SHERPA_ONNX_LOGE("sdk api version: %s, driver version: %s", v.api_version,
v.drv_version);
}
rknn_custom_string custom_string =
GetCustomString(encoder_ctx_, config_.debug);
rknn_input_output_num io_num;
ret = rknn_query(encoder_ctx_, RKNN_QUERY_IN_OUT_NUM, &io_num,
sizeof(io_num));
SHERPA_ONNX_RKNN_CHECK(ret,
"Failed to get I/O information for the encoder");
if (config_.debug) {
SHERPA_ONNX_LOGE("encoder: %d inputs, %d outputs",
static_cast<int32_t>(io_num.n_input),
static_cast<int32_t>(io_num.n_output));
}
encoder_input_attrs_.resize(io_num.n_input);
encoder_output_attrs_.resize(io_num.n_output);
int32_t i = 0;
for (auto &attr : encoder_input_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(encoder_ctx_, RKNN_QUERY_INPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for encoder input %d", i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : encoder_input_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Encoder inputs info----------\n%s",
os.str().c_str());
}
i = 0;
for (auto &attr : encoder_output_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(encoder_ctx_, RKNN_QUERY_OUTPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for encoder output %d",
i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : encoder_output_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Encoder outputs info----------\n%s",
os.str().c_str());
}
rknn_custom_string custom_string;
ret = rknn_query(encoder_ctx_, RKNN_QUERY_CUSTOM_STRING, &custom_string,
sizeof(custom_string));
SHERPA_ONNX_RKNN_CHECK(
ret, "Failed to read custom string from the encoder model");
if (config_.debug) {
SHERPA_ONNX_LOGE("customs string: %s", custom_string.string);
}
auto meta = Parse(custom_string);
if (config_.debug) {
for (const auto &p : meta) {
SHERPA_ONNX_LOGE("%s: %s", p.first.c_str(), p.second.c_str());
}
}
auto meta = Parse(custom_string, config_.debug);
if (meta.count("encoder_dims")) {
SplitStringToIntegers(meta.at("encoder_dims"), ",", false,
@@ -479,58 +367,10 @@ class OnlineZipformerTransducerModelRknn::Impl {
}
void InitDecoder(void *model_data, size_t model_data_length) {
auto ret =
rknn_init(&decoder_ctx_, model_data, model_data_length, 0, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to init decoder '%s'",
config_.transducer.decoder.c_str());
InitContext(model_data, model_data_length, config_.debug, &decoder_ctx_);
rknn_input_output_num io_num;
ret = rknn_query(decoder_ctx_, RKNN_QUERY_IN_OUT_NUM, &io_num,
sizeof(io_num));
SHERPA_ONNX_RKNN_CHECK(ret,
"Failed to get I/O information for the decoder");
if (io_num.n_input != 1) {
SHERPA_ONNX_LOGE("Expect only 1 decoder input. Given %d",
static_cast<int32_t>(io_num.n_input));
SHERPA_ONNX_EXIT(-1);
}
if (io_num.n_output != 1) {
SHERPA_ONNX_LOGE("Expect only 1 decoder output. Given %d",
static_cast<int32_t>(io_num.n_output));
SHERPA_ONNX_EXIT(-1);
}
if (config_.debug) {
SHERPA_ONNX_LOGE("decoder: %d inputs, %d outputs",
static_cast<int32_t>(io_num.n_input),
static_cast<int32_t>(io_num.n_output));
}
decoder_input_attrs_.resize(io_num.n_input);
decoder_output_attrs_.resize(io_num.n_output);
int32_t i = 0;
for (auto &attr : decoder_input_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(decoder_ctx_, RKNN_QUERY_INPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for decoder input %d", i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : decoder_input_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Decoder inputs info----------\n%s",
os.str().c_str());
}
InitInputOutputAttrs(decoder_ctx_, config_.debug, &decoder_input_attrs_,
&decoder_output_attrs_);
if (decoder_input_attrs_[0].type != RKNN_TENSOR_INT64) {
SHERPA_ONNX_LOGE("Expect int64 for decoder input. Given: %d, %s",
@@ -543,90 +383,13 @@ class OnlineZipformerTransducerModelRknn::Impl {
if (config_.debug) {
SHERPA_ONNX_LOGE("context_size: %d", context_size_);
}
i = 0;
for (auto &attr : decoder_output_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(decoder_ctx_, RKNN_QUERY_OUTPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for decoder output %d",
i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : decoder_output_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Decoder outputs info----------\n%s",
os.str().c_str());
}
}
void InitJoiner(void *model_data, size_t model_data_length) {
auto ret =
rknn_init(&joiner_ctx_, model_data, model_data_length, 0, nullptr);
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to init joiner '%s'",
config_.transducer.joiner.c_str());
InitContext(model_data, model_data_length, config_.debug, &joiner_ctx_);
rknn_input_output_num io_num;
ret =
rknn_query(joiner_ctx_, RKNN_QUERY_IN_OUT_NUM, &io_num, sizeof(io_num));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get I/O information for the joiner");
if (config_.debug) {
SHERPA_ONNX_LOGE("joiner: %d inputs, %d outputs",
static_cast<int32_t>(io_num.n_input),
static_cast<int32_t>(io_num.n_output));
}
joiner_input_attrs_.resize(io_num.n_input);
joiner_output_attrs_.resize(io_num.n_output);
int32_t i = 0;
for (auto &attr : joiner_input_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret = rknn_query(joiner_ctx_, RKNN_QUERY_INPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for joiner input %d", i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : joiner_input_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Joiner inputs info----------\n%s",
os.str().c_str());
}
i = 0;
for (auto &attr : joiner_output_attrs_) {
memset(&attr, 0, sizeof(attr));
attr.index = i;
ret =
rknn_query(joiner_ctx_, RKNN_QUERY_OUTPUT_ATTR, &attr, sizeof(attr));
SHERPA_ONNX_RKNN_CHECK(ret, "Failed to get attr for joiner output %d", i);
i += 1;
}
if (config_.debug) {
std::ostringstream os;
std::string sep;
for (auto &attr : joiner_output_attrs_) {
os << sep << ToString(attr);
sep = "\n";
}
SHERPA_ONNX_LOGE("\n----------Joiner outputs info----------\n%s",
os.str().c_str());
}
InitInputOutputAttrs(joiner_ctx_, config_.debug, &joiner_input_attrs_,
&joiner_output_attrs_);
vocab_size_ = joiner_output_attrs_[0].dims[1];
if (config_.debug) {