forked from extern/whisper.cpp
stream : partial encoder experiments
This commit is contained in:
parent
2ba66360c9
commit
c058aaf22e
@ -221,6 +221,7 @@ int main(int argc, char ** argv) {
|
||||
const int n_samples = (params.step_ms/1000.0)*WHISPER_SAMPLE_RATE;
|
||||
const int n_samples_len = (params.length_ms/1000.0)*WHISPER_SAMPLE_RATE;
|
||||
const int n_samples_30s = 30*WHISPER_SAMPLE_RATE;
|
||||
const int n_samples_keep = 0.2*WHISPER_SAMPLE_RATE;
|
||||
|
||||
std::vector<float> pcmf32(n_samples_30s, 0.0f);
|
||||
std::vector<float> pcmf32_old;
|
||||
@ -303,7 +304,7 @@ int main(int argc, char ** argv) {
|
||||
//const int n_samples_take = std::min((int) pcmf32_old.size(), std::max(0, n_samples_30s/30 - n_samples_new));
|
||||
|
||||
// take up to params.length_ms audio from previous iteration
|
||||
const int n_samples_take = std::min((int) pcmf32_old.size(), std::max(0, n_samples_len - n_samples_new));
|
||||
const int n_samples_take = std::min((int) pcmf32_old.size(), std::max(0, n_samples_keep + n_samples_len - n_samples_new));
|
||||
|
||||
//printf("processing: take = %d, new = %d, old = %d\n", n_samples_take, n_samples_new, (int) pcmf32_old.size());
|
||||
|
||||
@ -379,7 +380,8 @@ int main(int argc, char ** argv) {
|
||||
if ((n_iter % n_new_line) == 0) {
|
||||
printf("\n");
|
||||
|
||||
pcmf32_old.clear();
|
||||
// keep part of the audio for next iteration to try to mitigate word boundary issues
|
||||
pcmf32_old = std::vector<float>(pcmf32.end() - n_samples_keep, pcmf32.end());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
67
whisper.cpp
67
whisper.cpp
@ -613,7 +613,7 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
|
||||
const int n_audio_state = hparams.n_audio_state;
|
||||
const int n_audio_layer = hparams.n_audio_layer;
|
||||
|
||||
const int n_text_ctx = hparams.n_text_ctx;
|
||||
const int n_text_ctx = hparams.n_text_ctx;
|
||||
const int n_text_state = hparams.n_text_state;
|
||||
const int n_text_layer = hparams.n_text_layer;
|
||||
|
||||
@ -748,7 +748,7 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
|
||||
const int n_audio_state = hparams.n_audio_state;
|
||||
const int n_audio_layer = hparams.n_audio_layer;
|
||||
|
||||
const int n_text_ctx = hparams.n_text_ctx;
|
||||
const int n_text_ctx = hparams.n_text_ctx;
|
||||
const int n_text_state = hparams.n_text_state;
|
||||
const int n_text_layer = hparams.n_text_layer;
|
||||
|
||||
@ -967,13 +967,16 @@ static bool whisper_model_load(const std::string & fname, whisper_context & wctx
|
||||
|
||||
// key/value memory for the cross-attention layer
|
||||
{
|
||||
const int n_audio_ctx = hparams.n_audio_ctx;
|
||||
const int n_audio_ctx = hparams.n_audio_ctx;
|
||||
|
||||
const int n_mem = n_text_layer*n_audio_ctx;
|
||||
const int n_elements = n_text_state*n_mem;
|
||||
|
||||
model.memory_cross_k = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
|
||||
model.memory_cross_v = ggml_new_tensor_1d(ctx, GGML_TYPE_F16, n_elements);
|
||||
|
||||
//memset(model.memory_cross_k->data, 0, ggml_nbytes(model.memory_cross_k));
|
||||
//memset(model.memory_cross_v->data, 0, ggml_nbytes(model.memory_cross_v));
|
||||
}
|
||||
|
||||
const size_t memory_size =
|
||||
@ -1076,13 +1079,11 @@ static bool whisper_encode(
|
||||
const auto & mel_inp = wctx.mel;
|
||||
const auto & hparams = model.hparams;
|
||||
|
||||
const int n_ctx = hparams.n_audio_ctx;
|
||||
const int n_ctx = WHISPER_EXPERIMENT_AUDIO_CTX;
|
||||
const int n_state = hparams.n_audio_state;
|
||||
const int n_head = hparams.n_audio_head;
|
||||
const int n_layer = hparams.n_audio_layer;
|
||||
|
||||
const int N = n_ctx;
|
||||
|
||||
const int n_mels = hparams.n_mels;
|
||||
assert(mel_inp.n_mel == n_mels);
|
||||
|
||||
@ -1132,7 +1133,24 @@ static bool whisper_encode(
|
||||
cur = ggml_gelu(ctx0, cur);
|
||||
}
|
||||
|
||||
cur = ggml_add(ctx0, model.e_pe, ggml_transpose(ctx0, cur));
|
||||
//static int iter = -1;
|
||||
//const int n_iter = 1500/n_ctx;
|
||||
|
||||
//iter = (iter + 1) % n_iter;
|
||||
|
||||
//if (iter == 0) {
|
||||
// memset(model.memory_cross_k->data, 0, ggml_nbytes(model.memory_cross_k));
|
||||
// memset(model.memory_cross_v->data, 0, ggml_nbytes(model.memory_cross_v));
|
||||
//}
|
||||
|
||||
static int iter = 0;
|
||||
|
||||
const size_t e_pe_stride = model.e_pe->ne[0]*ggml_element_size(model.e_pe);
|
||||
const size_t e_pe_offset = model.e_pe->ne[0]*ggml_element_size(model.e_pe)*n_ctx*iter;
|
||||
|
||||
struct ggml_tensor * e_pe = ggml_view_2d(ctx0, model.e_pe, model.e_pe->ne[0], n_ctx, e_pe_stride, e_pe_offset);
|
||||
|
||||
cur = ggml_add(ctx0, e_pe, ggml_transpose(ctx0, cur));
|
||||
|
||||
struct ggml_tensor * inpL = cur;
|
||||
|
||||
@ -1198,14 +1216,14 @@ static bool whisper_encode(
|
||||
ggml_permute(ctxL,
|
||||
ggml_cpy(ctxL,
|
||||
Qcur,
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, N)),
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, n_ctx)),
|
||||
0, 2, 1, 3);
|
||||
|
||||
struct ggml_tensor * K =
|
||||
ggml_permute(ctxL,
|
||||
ggml_cpy(ctxL,
|
||||
Kcur,
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, N)),
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, n_ctx)),
|
||||
0, 2, 1, 3);
|
||||
|
||||
struct ggml_tensor * V =
|
||||
@ -1213,9 +1231,9 @@ static bool whisper_encode(
|
||||
ggml_permute(ctxL,
|
||||
ggml_reshape_3d(ctxL,
|
||||
Vcur,
|
||||
n_state/n_head, n_head, N),
|
||||
n_state/n_head, n_head, n_ctx),
|
||||
1, 2, 0, 3),
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, N, n_state/n_head, n_head)
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_ctx, n_state/n_head, n_head)
|
||||
);
|
||||
|
||||
struct ggml_tensor * KQV = ggml_flash_attn(ctxL, Q, K, V, false);
|
||||
@ -1224,14 +1242,14 @@ static bool whisper_encode(
|
||||
ggml_permute(ctxL,
|
||||
ggml_cpy(ctxL,
|
||||
Qcur,
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F32, n_state/n_head, n_head, N)),
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F32, n_state/n_head, n_head, n_ctx)),
|
||||
0, 2, 1, 3);
|
||||
|
||||
struct ggml_tensor * K =
|
||||
ggml_permute(ctxL,
|
||||
ggml_cpy(ctxL,
|
||||
Kcur,
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, N)),
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, n_ctx)),
|
||||
0, 2, 1, 3);
|
||||
|
||||
// K * Q
|
||||
@ -1249,7 +1267,7 @@ static bool whisper_encode(
|
||||
// ggml_permute(ctxL,
|
||||
// ggml_cpy(ctxL,
|
||||
// Vcur,
|
||||
// ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, N)),
|
||||
// ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_head, n_ctx)),
|
||||
// 1, 2, 0, 3);
|
||||
|
||||
//struct ggml_tensor * KQV = ggml_mul_mat(ctxL, V_trans, KQ_soft_max);
|
||||
@ -1259,9 +1277,9 @@ static bool whisper_encode(
|
||||
ggml_permute(ctxL,
|
||||
ggml_reshape_3d(ctxL,
|
||||
Vcur,
|
||||
n_state/n_head, n_head, N),
|
||||
n_state/n_head, n_head, n_ctx),
|
||||
0, 2, 1, 3),
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, N, n_head)
|
||||
ggml_new_tensor_3d(ctxL, GGML_TYPE_F16, n_state/n_head, n_ctx, n_head)
|
||||
);
|
||||
|
||||
struct ggml_tensor * KQV = ggml_mul_mat(ctxL, ggml_transpose(ctxL, V), KQ_soft_max);
|
||||
@ -1271,7 +1289,7 @@ static bool whisper_encode(
|
||||
|
||||
cur = ggml_cpy(ctxL,
|
||||
KQV_merged,
|
||||
ggml_new_tensor_2d(ctxL, GGML_TYPE_F32, n_state, N));
|
||||
ggml_new_tensor_2d(ctxL, GGML_TYPE_F32, n_state, n_ctx));
|
||||
}
|
||||
|
||||
// projection
|
||||
@ -1425,6 +1443,8 @@ static bool whisper_encode(
|
||||
Vcross),
|
||||
Vcross);
|
||||
|
||||
//struct ggml_tensor * k = ggml_view_1d(ctx0, model.memory_cross_k, n_state*n_ctx, (ggml_element_size(model.memory_cross_k)*n_state)*(il*hparams.n_audio_ctx + iter*n_ctx));
|
||||
//struct ggml_tensor * v = ggml_view_1d(ctx0, model.memory_cross_v, n_state*n_ctx, (ggml_element_size(model.memory_cross_v)*n_state)*(il*hparams.n_audio_ctx + iter*n_ctx));
|
||||
struct ggml_tensor * k = ggml_view_1d(ctx0, model.memory_cross_k, n_state*n_ctx, (ggml_element_size(model.memory_cross_k)*n_state)*(il*n_ctx));
|
||||
struct ggml_tensor * v = ggml_view_1d(ctx0, model.memory_cross_v, n_state*n_ctx, (ggml_element_size(model.memory_cross_v)*n_state)*(il*n_ctx));
|
||||
|
||||
@ -1474,7 +1494,8 @@ static bool whisper_decode(
|
||||
const int n_layer = hparams.n_text_layer;
|
||||
|
||||
const int N = n_tokens;
|
||||
const int M = hparams.n_audio_ctx;
|
||||
//const int M = hparams.n_audio_ctx;
|
||||
const int M = WHISPER_EXPERIMENT_AUDIO_CTX;
|
||||
|
||||
struct ggml_init_params params = {
|
||||
.mem_size = wctx.buf_compute.size(),
|
||||
@ -2662,7 +2683,7 @@ int whisper_full(
|
||||
//}
|
||||
|
||||
// end of text token
|
||||
if (token.id == whisper_token_eot(ctx)) {
|
||||
if (token.id == whisper_token_eot(ctx) || (i > WHISPER_EXPERIMENT_MAX_TOKENS_PER_SEGMENT)) {
|
||||
if (result_len == 0) {
|
||||
if (seek + seek_delta + 100 >= seek_end) {
|
||||
result_len = i + 1;
|
||||
@ -2671,6 +2692,12 @@ int whisper_full(
|
||||
fprintf(stderr, "\n%s: failed to generate timestamp token - this should not happen\n\n", __func__);
|
||||
}
|
||||
}
|
||||
|
||||
// TODO: TMP TO MAKE STREAM WORK ON RPI4 ===
|
||||
result_len = i + 1;
|
||||
seek_delta = 100*WHISPER_CHUNK_SIZE;
|
||||
// =========================================
|
||||
|
||||
break;
|
||||
}
|
||||
|
||||
@ -2850,7 +2877,7 @@ int whisper_full_parallel(
|
||||
|
||||
// key/value memory for the cross-attention layer
|
||||
{
|
||||
const int n_audio_ctx = hparams.n_audio_ctx;
|
||||
const int n_audio_ctx = hparams.n_audio_ctx;
|
||||
|
||||
const int n_mem = n_text_layer*n_audio_ctx;
|
||||
const int n_elements = n_text_state*n_mem;
|
||||
|
Loading…
Reference in New Issue
Block a user