Merge branch 'master' into ggml-backend-no-sched

This commit is contained in:
Georgi Gerganov 2023-11-10 13:21:47 +02:00
commit 0ab5025316
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7 changed files with 15 additions and 8 deletions

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@ -123,7 +123,7 @@ API_AVAILABLE(macos(12.0), ios(15.0), watchos(8.0), tvos(15.0)) __attribute__((v
/**
Make a prediction using the convenience interface
@param logmel_data as 1 × 80 × 3000 3-dimensional array of floats:
@param logmel_data as 1 × n_mel × 3000 3-dimensional array of floats:
@param error If an error occurs, upon return contains an NSError object that describes the problem. If you are not interested in possible errors, pass in NULL.
@return the prediction as whisper_encoder_implOutput
*/

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@ -3,6 +3,8 @@
// Code is derived from the work of Github user @wangchou
// ref: https://github.com/wangchou/callCoreMLFromCpp
#include <stdint.h>
#if __cplusplus
extern "C" {
#endif
@ -14,6 +16,8 @@ void whisper_coreml_free(struct whisper_coreml_context * ctx);
void whisper_coreml_encode(
const whisper_coreml_context * ctx,
int64_t n_ctx,
int64_t n_mel,
float * mel,
float * out);

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@ -48,13 +48,15 @@ void whisper_coreml_free(struct whisper_coreml_context * ctx) {
void whisper_coreml_encode(
const whisper_coreml_context * ctx,
int64_t n_ctx,
int64_t n_mel,
float * mel,
float * out) {
MLMultiArray * inMultiArray = [
[MLMultiArray alloc] initWithDataPointer: mel
shape: @[@1, @80, @3000]
shape: @[@1, @(n_mel), @(n_ctx)]
dataType: MLMultiArrayDataTypeFloat32
strides: @[@(240000), @(3000), @1]
strides: @[@(n_ctx*n_mel), @(n_ctx), @1]
deallocator: nil
error: nil
];

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@ -248,7 +248,7 @@ int main(int argc, char ** argv) {
return 1;
}
if (whisper_lang_id(params.language.c_str()) == -1) {
if (params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1) {
fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
whisper_print_usage(argc, argv, params);
exit(0);

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@ -252,7 +252,7 @@ class WhisperANE(Whisper):
def convert_encoder(hparams, model, quantize=False):
model.eval()
input_shape = (1, 80, 3000)
input_shape = (1, hparams.n_mels, 3000)
input_data = torch.randn(input_shape)
traced_model = torch.jit.trace(model, input_data)
@ -302,7 +302,7 @@ if __name__ == "__main__":
parser.add_argument("--optimize-ane", type=bool, help="optimize for ANE execution (currently broken)", default=False)
args = parser.parse_args()
if args.model not in ["tiny", "tiny.en", "base", "base.en", "small", "small.en", "medium", "medium.en", "large", "large-v1", "large-v2"]:
if args.model not in ["tiny", "tiny.en", "base", "base.en", "small", "small.en", "small.en-tdrz", "medium", "medium.en", "large", "large-v1", "large-v2"]:
raise ValueError("Invalid model name")
whisper = load_model(args.model).cpu()

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@ -9,7 +9,7 @@ import shutil
def convert_encoder(hparams, encoder, mname):
encoder.eval()
mel = torch.zeros((1, 80, 3000))
mel = torch.zeros((1, hparams.n_mels, 3000))
onnx_folder=os.path.join(os.path.dirname(__file__),"onnx_encoder")

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@ -1639,7 +1639,7 @@ static struct ggml_cgraph * whisper_build_graph_conv(
ggml_allocr_alloc(alloc, cur);
if (!ggml_allocr_is_measure(alloc)) {
whisper_coreml_encode(wstate.ctx_coreml, (float *) mel->data, (float *) cur->data);
whisper_coreml_encode(wstate.ctx_coreml, mel->ne[0], mel->ne[1], (float *) mel->data, (float *) cur->data);
}
#endif
#ifdef WHISPER_USE_OPENVINO
@ -3708,6 +3708,7 @@ void whisper_print_timings(struct whisper_context * ctx) {
void whisper_reset_timings(struct whisper_context * ctx) {
ctx->t_start_us = ggml_time_us();
if (ctx->state != nullptr) {
ctx->state->t_mel_us = 0;
ctx->state->t_sample_us = 0;
ctx->state->t_encode_us = 0;
ctx->state->t_decode_us = 0;