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e76326e3e0
| Author | SHA1 | Date | |
|---|---|---|---|
|
e76326e3e0 |
@ -34,7 +34,6 @@ endforeach()
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add_executable(${TARGET} ${TARGET_SRCS})
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install(TARGETS ${TARGET} RUNTIME)
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target_include_directories(${TARGET} PRIVATE ${CMAKE_SOURCE_DIR})
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target_link_libraries(${TARGET} PRIVATE common ${CMAKE_THREAD_LIBS_INIT})
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if (LLAMA_SERVER_SSL)
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@ -450,8 +450,6 @@ These words will not be included in the completion, so make sure to add them to
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`post_sampling_probs`: Returns the probabilities of top `n_probs` tokens after applying sampling chain.
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`response_fields`: A list of response fields, for example: `"response_fields": ["content", "generation_settings/n_predict"]`. If the specified field is missing, it will simply be omitted from the response without triggering an error.
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**Response format**
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- Note: In streaming mode (`stream`), only `content`, `tokens` and `stop` will be returned until end of completion. Responses are sent using the [Server-sent events](https://html.spec.whatwg.org/multipage/server-sent-events.html) standard. Note: the browser's `EventSource` interface cannot be used due to its lack of `POST` request support.
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@ -92,7 +92,6 @@ struct slot_params {
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int64_t t_max_predict_ms = -1; // if positive, limit the generation phase to this time limit
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std::vector<std::string> antiprompt;
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std::vector<std::string> response_fields;
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bool timings_per_token = false;
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bool post_sampling_probs = false;
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bool ignore_eos = false;
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@ -210,7 +209,6 @@ struct server_task {
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params.n_discard = json_value(data, "n_discard", defaults.n_discard);
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//params.t_max_prompt_ms = json_value(data, "t_max_prompt_ms", defaults.t_max_prompt_ms); // TODO: implement
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params.t_max_predict_ms = json_value(data, "t_max_predict_ms", defaults.t_max_predict_ms);
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params.response_fields = json_value(data, "response_fields", std::vector<std::string>());
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params.sampling.top_k = json_value(data, "top_k", defaults.sampling.top_k);
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params.sampling.top_p = json_value(data, "top_p", defaults.sampling.top_p);
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@ -524,7 +522,6 @@ struct server_task_result_cmpl_final : server_task_result {
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bool post_sampling_probs;
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std::vector<completion_token_output> probs_output;
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std::vector<std::string> response_fields;
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slot_params generation_params;
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@ -571,7 +568,7 @@ struct server_task_result_cmpl_final : server_task_result {
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if (!stream && !probs_output.empty()) {
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res["completion_probabilities"] = completion_token_output::probs_vector_to_json(probs_output, post_sampling_probs);
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}
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return response_fields.empty() ? res : json_get_nested_values(response_fields, res);
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return res;
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}
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json to_json_oaicompat_chat() {
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@ -2069,7 +2066,6 @@ struct server_context {
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res->tokens = slot.generated_tokens;
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res->timings = slot.get_timings();
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res->prompt = common_detokenize(ctx, slot.prompt_tokens, true);
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res->response_fields = slot.params.response_fields;
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res->truncated = slot.truncated;
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res->n_decoded = slot.n_decoded;
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@ -3790,17 +3786,6 @@ int main(int argc, char ** argv) {
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return;
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}
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bool use_base64 = false;
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if (body.count("encoding_format") != 0) {
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const std::string& format = body.at("encoding_format");
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if (format == "base64") {
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use_base64 = true;
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} else if (format != "float") {
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res_error(res, format_error_response("The format to return the embeddings in. Can be either float or base64", ERROR_TYPE_INVALID_REQUEST));
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return;
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}
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}
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std::vector<llama_tokens> tokenized_prompts = tokenize_input_prompts(ctx_server.ctx, prompt, true, true);
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for (const auto & tokens : tokenized_prompts) {
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// this check is necessary for models that do not add BOS token to the input
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@ -3852,7 +3837,7 @@ int main(int argc, char ** argv) {
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}
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// write JSON response
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json root = oaicompat ? format_embeddings_response_oaicompat(body, responses, use_base64) : json(responses);
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json root = oaicompat ? format_embeddings_response_oaicompat(body, responses) : json(responses);
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res_ok(res, root);
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};
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@ -95,7 +95,7 @@ def test_consistent_result_same_seed(n_slots: int):
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res = server.make_request("POST", "/completion", data={
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"prompt": "I believe the meaning of life is",
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"seed": 42,
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"temperature": 0.0,
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"temperature": 1.0,
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"cache_prompt": False, # TODO: remove this once test_cache_vs_nocache_prompt is fixed
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})
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if last_res is not None:
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@ -120,10 +120,9 @@ def test_different_result_different_seed(n_slots: int):
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assert res.body["content"] != last_res.body["content"]
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last_res = res
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# TODO figure why it don't work with temperature = 1
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# @pytest.mark.parametrize("temperature", [0.0, 1.0])
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@pytest.mark.parametrize("n_batch", [16, 32])
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@pytest.mark.parametrize("temperature", [0.0])
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@pytest.mark.parametrize("temperature", [0.0, 1.0])
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def test_consistent_result_different_batch_size(n_batch: int, temperature: float):
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global server
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server.n_batch = n_batch
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@ -258,40 +257,6 @@ def test_completion_parallel_slots(n_slots: int, n_requests: int):
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# assert match_regex(re_content, res.body["content"])
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@pytest.mark.parametrize(
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"prompt,n_predict,response_fields",
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[
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("I believe the meaning of life is", 8, []),
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("I believe the meaning of life is", 32, ["content", "generation_settings/n_predict", "prompt"]),
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],
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)
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def test_completion_response_fields(
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prompt: str, n_predict: int, response_fields: list[str]
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):
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global server
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server.start()
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res = server.make_request(
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"POST",
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"/completion",
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data={
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"n_predict": n_predict,
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"prompt": prompt,
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"response_fields": response_fields,
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},
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)
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assert res.status_code == 200
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assert "content" in res.body
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assert len(res.body["content"])
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if len(response_fields):
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assert res.body["generation_settings/n_predict"] == n_predict
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assert res.body["prompt"] == "<s> " + prompt
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assert isinstance(res.body["content"], str)
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assert len(res.body) == len(response_fields)
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else:
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assert len(res.body)
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assert "generation_settings" in res.body
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def test_n_probs():
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global server
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server.start()
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@ -1,5 +1,3 @@
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import base64
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import struct
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import pytest
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from openai import OpenAI
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from utils import *
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@ -196,42 +194,3 @@ def test_embedding_usage_multiple():
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assert res.status_code == 200
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assert res.body['usage']['prompt_tokens'] == res.body['usage']['total_tokens']
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assert res.body['usage']['prompt_tokens'] == 2 * 9
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def test_embedding_openai_library_base64():
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server.start()
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test_input = "Test base64 embedding output"
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# get embedding in default format
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res = server.make_request("POST", "/v1/embeddings", data={
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"input": test_input
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})
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assert res.status_code == 200
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vec0 = res.body["data"][0]["embedding"]
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# get embedding in base64 format
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res = server.make_request("POST", "/v1/embeddings", data={
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"input": test_input,
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"encoding_format": "base64"
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})
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assert res.status_code == 200
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assert "data" in res.body
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assert len(res.body["data"]) == 1
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embedding_data = res.body["data"][0]
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assert "embedding" in embedding_data
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assert isinstance(embedding_data["embedding"], str)
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# Verify embedding is valid base64
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decoded = base64.b64decode(embedding_data["embedding"])
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# Verify decoded data can be converted back to float array
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float_count = len(decoded) // 4 # 4 bytes per float
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floats = struct.unpack(f'{float_count}f', decoded)
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assert len(floats) > 0
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assert all(isinstance(x, float) for x in floats)
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assert len(floats) == len(vec0)
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# make sure the decoded data is the same as the original
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for x, y in zip(floats, vec0):
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assert abs(x - y) < EPSILON
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@ -3,7 +3,6 @@
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#include "common.h"
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#include "log.h"
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#include "llama.h"
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#include "common/base64.hpp"
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#ifndef NDEBUG
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// crash the server in debug mode, otherwise send an http 500 error
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@ -91,28 +90,6 @@ static bool json_is_array_of_mixed_numbers_strings(const json & data) {
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return false;
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}
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// get value by path(key1 / key2)
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static json json_get_nested_values(const std::vector<std::string> & paths, const json & js) {
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json result = json::object();
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for (const std::string & path : paths) {
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json current = js;
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const auto keys = string_split<std::string>(path, /*separator*/ '/');
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bool valid_path = true;
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for (const std::string & k : keys) {
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if (valid_path && current.is_object() && current.contains(k)) {
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current = current[k];
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} else {
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valid_path = false;
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}
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}
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if (valid_path) {
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result[path] = current;
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}
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}
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return result;
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}
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/**
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* this handles 2 cases:
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* - only string, example: "string"
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@ -614,31 +591,16 @@ static json oaicompat_completion_params_parse(
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return llama_params;
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}
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static json format_embeddings_response_oaicompat(const json & request, const json & embeddings, bool use_base64 = false) {
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static json format_embeddings_response_oaicompat(const json & request, const json & embeddings) {
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json data = json::array();
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int32_t n_tokens = 0;
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int i = 0;
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for (const auto & elem : embeddings) {
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json embedding_obj;
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if (use_base64) {
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const auto& vec = json_value(elem, "embedding", json::array()).get<std::vector<float>>();
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const char* data_ptr = reinterpret_cast<const char*>(vec.data());
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size_t data_size = vec.size() * sizeof(float);
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embedding_obj = {
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{"embedding", base64::encode(data_ptr, data_size)},
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{"index", i++},
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{"object", "embedding"},
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{"encoding_format", "base64"}
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};
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} else {
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embedding_obj = {
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{"embedding", json_value(elem, "embedding", json::array())},
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{"index", i++},
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{"object", "embedding"}
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};
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}
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data.push_back(embedding_obj);
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data.push_back(json{
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{"embedding", json_value(elem, "embedding", json::array())},
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{"index", i++},
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{"object", "embedding"}
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});
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n_tokens += json_value(elem, "tokens_evaluated", 0);
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}
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@ -234,7 +234,6 @@ function(ggml_add_backend_library backend)
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# write the shared library to the output directory
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set_target_properties(${backend} PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${CMAKE_RUNTIME_OUTPUT_DIRECTORY})
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target_compile_definitions(${backend} PRIVATE GGML_BACKEND_DL)
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add_dependencies(ggml ${backend})
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else()
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add_library(${backend} ${ARGN})
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target_link_libraries(ggml PUBLIC ${backend})
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@ -66,26 +66,6 @@
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#include "ggml-kompute.h"
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#endif
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// disable C++17 deprecation warning for std::codecvt_utf8
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#if defined(__clang__)
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# pragma clang diagnostic push
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# pragma clang diagnostic ignored "-Wdeprecated-declarations"
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#endif
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static std::wstring utf8_to_utf16(const std::string & str) {
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std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
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return converter.from_bytes(str);
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}
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static std::string utf16_to_utf8(const std::wstring & str) {
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std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
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return converter.to_bytes(str);
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}
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#if defined(__clang__)
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# pragma clang diagnostic pop
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#endif
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#ifdef _WIN32
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using dl_handle = std::remove_pointer_t<HMODULE>;
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@ -108,6 +88,11 @@ static dl_handle * dl_load_library(const std::wstring & path) {
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return handle;
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}
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static dl_handle * dl_load_library(const std::string & path) {
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std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
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return dl_load_library(converter.from_bytes(path));
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}
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static void * dl_get_sym(dl_handle * handle, const char * name) {
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DWORD old_mode = SetErrorMode(SEM_FAILCRITICALERRORS);
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SetErrorMode(old_mode | SEM_FAILCRITICALERRORS);
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@ -129,8 +114,8 @@ struct dl_handle_deleter {
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}
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};
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static void * dl_load_library(const std::wstring & path) {
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dl_handle * handle = dlopen(utf16_to_utf8(path).c_str(), RTLD_NOW | RTLD_LOCAL);
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static void * dl_load_library(const std::string & path) {
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dl_handle * handle = dlopen(path.c_str(), RTLD_NOW | RTLD_LOCAL);
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return handle;
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}
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@ -217,11 +202,11 @@ struct ggml_backend_registry {
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devices.push_back(device);
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}
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ggml_backend_reg_t load_backend(const std::wstring & path, bool silent) {
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ggml_backend_reg_t load_backend(const char * path, bool silent) {
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dl_handle_ptr handle { dl_load_library(path) };
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if (!handle) {
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if (!silent) {
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GGML_LOG_ERROR("%s: failed to load %s\n", __func__, utf16_to_utf8(path).c_str());
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GGML_LOG_ERROR("%s: failed to load %s\n", __func__, path);
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}
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return nullptr;
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}
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@ -229,7 +214,7 @@ struct ggml_backend_registry {
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auto score_fn = (ggml_backend_score_t) dl_get_sym(handle.get(), "ggml_backend_score");
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if (score_fn && score_fn() == 0) {
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if (!silent) {
|
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GGML_LOG_INFO("%s: backend %s is not supported on this system\n", __func__, utf16_to_utf8(path).c_str());
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GGML_LOG_INFO("%s: backend %s is not supported on this system\n", __func__, path);
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}
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return nullptr;
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}
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@ -237,7 +222,7 @@ struct ggml_backend_registry {
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auto backend_init_fn = (ggml_backend_init_t) dl_get_sym(handle.get(), "ggml_backend_init");
|
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if (!backend_init_fn) {
|
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if (!silent) {
|
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GGML_LOG_ERROR("%s: failed to find ggml_backend_init in %s\n", __func__, utf16_to_utf8(path).c_str());
|
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GGML_LOG_ERROR("%s: failed to find ggml_backend_init in %s\n", __func__, path);
|
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}
|
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return nullptr;
|
||||
}
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||||
@ -246,16 +231,16 @@ struct ggml_backend_registry {
|
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if (!reg || reg->api_version != GGML_BACKEND_API_VERSION) {
|
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if (!silent) {
|
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if (!reg) {
|
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GGML_LOG_ERROR("%s: failed to initialize backend from %s: ggml_backend_init returned NULL\n", __func__, utf16_to_utf8(path).c_str());
|
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GGML_LOG_ERROR("%s: failed to initialize backend from %s: ggml_backend_init returned NULL\n", __func__, path);
|
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} else {
|
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GGML_LOG_ERROR("%s: failed to initialize backend from %s: incompatible API version (backend: %d, current: %d)\n",
|
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__func__, utf16_to_utf8(path).c_str(), reg->api_version, GGML_BACKEND_API_VERSION);
|
||||
__func__, path, reg->api_version, GGML_BACKEND_API_VERSION);
|
||||
}
|
||||
}
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
GGML_LOG_INFO("%s: loaded %s backend from %s\n", __func__, ggml_backend_reg_name(reg), utf16_to_utf8(path).c_str());
|
||||
GGML_LOG_INFO("%s: loaded %s backend from %s\n", __func__, ggml_backend_reg_name(reg), path);
|
||||
|
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register_backend(reg, std::move(handle));
|
||||
|
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@ -391,14 +376,14 @@ ggml_backend_t ggml_backend_init_best(void) {
|
||||
|
||||
// Dynamic loading
|
||||
ggml_backend_reg_t ggml_backend_load(const char * path) {
|
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return get_reg().load_backend(utf8_to_utf16(path), false);
|
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return get_reg().load_backend(path, false);
|
||||
}
|
||||
|
||||
void ggml_backend_unload(ggml_backend_reg_t reg) {
|
||||
get_reg().unload_backend(reg, true);
|
||||
}
|
||||
|
||||
static std::wstring get_executable_path() {
|
||||
static std::string get_executable_path() {
|
||||
#if defined(__APPLE__)
|
||||
// get executable path
|
||||
std::vector<char> path;
|
||||
@ -416,7 +401,7 @@ static std::wstring get_executable_path() {
|
||||
if (last_slash != std::string::npos) {
|
||||
base_path = base_path.substr(0, last_slash);
|
||||
}
|
||||
return utf8_to_utf16(base_path + "/");
|
||||
return base_path + "/";
|
||||
#elif defined(__linux__) || defined(__FreeBSD__)
|
||||
std::string base_path = ".";
|
||||
std::vector<char> path(1024);
|
||||
@ -442,63 +427,57 @@ static std::wstring get_executable_path() {
|
||||
path.resize(path.size() * 2);
|
||||
}
|
||||
|
||||
return utf8_to_utf16(base_path + "/");
|
||||
return base_path + "/";
|
||||
#elif defined(_WIN32)
|
||||
std::vector<wchar_t> path(MAX_PATH);
|
||||
DWORD len = GetModuleFileNameW(NULL, path.data(), path.size());
|
||||
std::vector<char> path(MAX_PATH);
|
||||
DWORD len = GetModuleFileNameA(NULL, path.data(), path.size());
|
||||
if (len == 0) {
|
||||
return {};
|
||||
return "";
|
||||
}
|
||||
std::wstring base_path(path.data(), len);
|
||||
std::string base_path(path.data(), len);
|
||||
// remove executable name
|
||||
auto last_slash = base_path.find_last_of('\\');
|
||||
if (last_slash != std::string::npos) {
|
||||
base_path = base_path.substr(0, last_slash);
|
||||
}
|
||||
return base_path + L"\\";
|
||||
#else
|
||||
return {};
|
||||
return base_path + "\\";
|
||||
#endif
|
||||
}
|
||||
|
||||
static std::wstring backend_filename_prefix() {
|
||||
static std::string backend_filename_prefix() {
|
||||
#ifdef _WIN32
|
||||
return L"ggml-";
|
||||
return "ggml-";
|
||||
#else
|
||||
return L"libggml-";
|
||||
return "libggml-";
|
||||
#endif
|
||||
}
|
||||
|
||||
static std::wstring backend_filename_suffix() {
|
||||
static std::string backend_filename_suffix() {
|
||||
#ifdef _WIN32
|
||||
return L".dll";
|
||||
return ".dll";
|
||||
#else
|
||||
return L".so";
|
||||
#endif
|
||||
}
|
||||
|
||||
static std::wstring path_separator() {
|
||||
#ifdef _WIN32
|
||||
return L"\\";
|
||||
#else
|
||||
return L"/";
|
||||
return ".so";
|
||||
#endif
|
||||
}
|
||||
|
||||
static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent, const char * user_search_path) {
|
||||
// enumerate all the files that match [lib]ggml-name-*.[so|dll] in the search paths
|
||||
// TODO: search system paths
|
||||
std::wstring file_prefix = backend_filename_prefix() + utf8_to_utf16(name) + L"-";
|
||||
std::vector<std::wstring> search_paths;
|
||||
std::string file_prefix = backend_filename_prefix() + name + "-";
|
||||
std::vector<std::string> search_paths;
|
||||
if (user_search_path == nullptr) {
|
||||
search_paths.push_back(L"." + path_separator());
|
||||
search_paths.push_back("./");
|
||||
search_paths.push_back(get_executable_path());
|
||||
} else {
|
||||
search_paths.push_back(utf8_to_utf16(user_search_path) + path_separator());
|
||||
#if defined(_WIN32)
|
||||
search_paths.push_back(std::string(user_search_path) + "\\");
|
||||
#else
|
||||
search_paths.push_back(std::string(user_search_path) + "/");
|
||||
#endif
|
||||
}
|
||||
|
||||
int best_score = 0;
|
||||
std::wstring best_path;
|
||||
std::string best_path;
|
||||
|
||||
namespace fs = std::filesystem;
|
||||
for (const auto & search_path : search_paths) {
|
||||
@ -508,27 +487,27 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
|
||||
fs::directory_iterator dir_it(search_path, fs::directory_options::skip_permission_denied);
|
||||
for (const auto & entry : dir_it) {
|
||||
if (entry.is_regular_file()) {
|
||||
std::wstring filename = entry.path().filename().wstring();
|
||||
std::wstring ext = entry.path().extension().wstring();
|
||||
std::string filename = entry.path().filename().string();
|
||||
std::string ext = entry.path().extension().string();
|
||||
if (filename.find(file_prefix) == 0 && ext == backend_filename_suffix()) {
|
||||
dl_handle_ptr handle { dl_load_library(entry.path().wstring()) };
|
||||
dl_handle_ptr handle { dl_load_library(entry.path().c_str()) };
|
||||
if (!handle && !silent) {
|
||||
GGML_LOG_ERROR("%s: failed to load %s\n", __func__, utf16_to_utf8(entry.path().wstring()).c_str());
|
||||
GGML_LOG_ERROR("%s: failed to load %s\n", __func__, entry.path().string().c_str());
|
||||
}
|
||||
if (handle) {
|
||||
auto score_fn = (ggml_backend_score_t) dl_get_sym(handle.get(), "ggml_backend_score");
|
||||
if (score_fn) {
|
||||
int s = score_fn();
|
||||
#ifndef NDEBUG
|
||||
GGML_LOG_DEBUG("%s: %s score: %d\n", __func__, utf16_to_utf8(entry.path().wstring()).c_str(), s);
|
||||
GGML_LOG_DEBUG("%s: %s score: %d\n", __func__, entry.path().string().c_str(), s);
|
||||
#endif
|
||||
if (s > best_score) {
|
||||
best_score = s;
|
||||
best_path = entry.path().wstring();
|
||||
best_path = entry.path().string();
|
||||
}
|
||||
} else {
|
||||
if (!silent) {
|
||||
GGML_LOG_INFO("%s: failed to find ggml_backend_score in %s\n", __func__, utf16_to_utf8(entry.path().wstring()).c_str());
|
||||
GGML_LOG_INFO("%s: failed to find ggml_backend_score in %s\n", __func__, entry.path().string().c_str());
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -540,15 +519,15 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
|
||||
if (best_score == 0) {
|
||||
// try to load the base backend
|
||||
for (const auto & search_path : search_paths) {
|
||||
std::wstring path = search_path + backend_filename_prefix() + utf8_to_utf16(name) + backend_filename_suffix();
|
||||
std::string path = search_path + backend_filename_prefix() + name + backend_filename_suffix();
|
||||
if (fs::exists(path)) {
|
||||
return get_reg().load_backend(path, silent);
|
||||
return get_reg().load_backend(path.c_str(), silent);
|
||||
}
|
||||
}
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
return get_reg().load_backend(best_path, silent);
|
||||
return get_reg().load_backend(best_path.c_str(), silent);
|
||||
}
|
||||
|
||||
void ggml_backend_load_all() {
|
||||
|
||||
@ -135,20 +135,14 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
|
||||
endif()
|
||||
|
||||
# show enabled features
|
||||
if (CMAKE_HOST_SYSTEM_NAME STREQUAL "Windows")
|
||||
set(FEAT_INPUT_FILE "NUL")
|
||||
else()
|
||||
set(FEAT_INPUT_FILE "/dev/null")
|
||||
endif()
|
||||
|
||||
execute_process(
|
||||
COMMAND ${CMAKE_C_COMPILER} ${ARCH_FLAGS} -dM -E -
|
||||
INPUT_FILE ${FEAT_INPUT_FILE}
|
||||
INPUT_FILE "/dev/null"
|
||||
OUTPUT_VARIABLE ARM_FEATURE
|
||||
RESULT_VARIABLE ARM_FEATURE_RESULT
|
||||
)
|
||||
if (ARM_FEATURE_RESULT)
|
||||
message(WARNING "Failed to get ARM features")
|
||||
message(FATAL_ERROR "Failed to get ARM features")
|
||||
else()
|
||||
foreach(feature DOTPROD SVE MATMUL_INT8 FMA FP16_VECTOR_ARITHMETIC)
|
||||
string(FIND "${ARM_FEATURE}" "__ARM_FEATURE_${feature} 1" feature_pos)
|
||||
@ -323,11 +317,6 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
|
||||
target_compile_definitions(${GGML_CPU_NAME} PRIVATE ${ARCH_DEFINITIONS})
|
||||
|
||||
if (GGML_BACKEND_DL)
|
||||
if (GGML_NATIVE)
|
||||
# the feature check relies on ARCH_DEFINITIONS, but it is not set with GGML_NATIVE
|
||||
message(FATAL_ERROR "GGML_NATIVE is not compatible with GGML_BACKEND_DL, consider using GGML_CPU_ALL_VARIANTS")
|
||||
endif()
|
||||
|
||||
# The feature detection code is compiled as a separate target so that
|
||||
# it can be built without the architecture flags
|
||||
# Since multiple variants of the CPU backend may be included in the same
|
||||
|
||||
@ -7419,14 +7419,14 @@ static void ggml_compute_forward_mul_mat(
|
||||
if (src1_cont) {
|
||||
for (int64_t i13 = 0; i13 < ne13; i13++)
|
||||
for (int64_t i12 = 0; i12 < ne12; i12++)
|
||||
if (!llamafile_sgemm(params,
|
||||
ne01, ne11, ne00/ggml_blck_size(src0->type),
|
||||
if (!llamafile_sgemm(ne01, ne11, ne00/ggml_blck_size(src0->type),
|
||||
(const char *)src0->data + i12/r2*nb02 + i13/r3*nb03,
|
||||
nb01/ggml_type_size(src0->type),
|
||||
(const char *)src1->data + i12*nb12 + i13*nb13,
|
||||
nb11/ggml_type_size(src1->type),
|
||||
(char *)dst->data + i12*nb2 + i13*nb3,
|
||||
nb1/ggml_type_size(dst->type),
|
||||
ith, nth,
|
||||
src0->type,
|
||||
src1->type,
|
||||
dst->type))
|
||||
@ -7471,14 +7471,14 @@ UseGgmlGemm1:;
|
||||
|
||||
for (int64_t i13 = 0; i13 < ne13; i13++)
|
||||
for (int64_t i12 = 0; i12 < ne12; i12++)
|
||||
if (!llamafile_sgemm(params,
|
||||
ne01, ne11, ne00/ggml_blck_size(src0->type),
|
||||
if (!llamafile_sgemm(ne01, ne11, ne00/ggml_blck_size(src0->type),
|
||||
(const char *)src0->data + i12/r2*nb02 + i13/r3*nb03,
|
||||
nb01/ggml_type_size(src0->type),
|
||||
(const char *)wdata + (i12*ne11 + i13*ne12*ne11)*row_size,
|
||||
row_size/ggml_type_size(vec_dot_type),
|
||||
(char *)dst->data + i12*nb2 + i13*nb3,
|
||||
nb1/ggml_type_size(dst->type),
|
||||
ith, nth,
|
||||
src0->type,
|
||||
vec_dot_type,
|
||||
dst->type))
|
||||
|
||||
@ -53,8 +53,6 @@
|
||||
#include "ggml-cpu-impl.h"
|
||||
#include "ggml-quants.h"
|
||||
|
||||
#include <atomic>
|
||||
|
||||
#ifdef _MSC_VER
|
||||
#define NOINLINE __declspec(noinline)
|
||||
#else
|
||||
@ -136,16 +134,6 @@ inline __m512 madd(__m512 a, __m512 b, __m512 c) {
|
||||
return _mm512_fmadd_ps(a, b, c);
|
||||
}
|
||||
#endif
|
||||
#if defined(__AVX512BF16__)
|
||||
template <>
|
||||
inline __m512 madd(__m512bh a, __m512bh b, __m512 c) {
|
||||
return _mm512_dpbf16_ps(c, a, b);
|
||||
}
|
||||
template <>
|
||||
inline __m256 madd(__m256bh a, __m256bh b, __m256 c) {
|
||||
return _mm256_dpbf16_ps(c, a, b);
|
||||
}
|
||||
#endif
|
||||
#endif
|
||||
|
||||
#if defined(__ARM_FEATURE_FMA)
|
||||
@ -238,13 +226,6 @@ template <> inline __m256 load(const float *p) {
|
||||
}
|
||||
#endif // __AVX__
|
||||
|
||||
#if defined(__AVX2__) || defined(__AVX512F__)
|
||||
template <> inline __m256 load(const ggml_bf16_t *p) {
|
||||
return _mm256_castsi256_ps(
|
||||
_mm256_slli_epi32(_mm256_cvtepu16_epi32(_mm_loadu_si128((const __m128i *)p)), 16));
|
||||
}
|
||||
#endif // __AVX2__
|
||||
|
||||
#if defined(__F16C__)
|
||||
template <> inline __m256 load(const ggml_fp16_t *p) {
|
||||
return _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)p));
|
||||
@ -258,27 +239,8 @@ template <> inline __m512 load(const float *p) {
|
||||
template <> inline __m512 load(const ggml_fp16_t *p) {
|
||||
return _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)p));
|
||||
}
|
||||
template <> inline __m512 load(const ggml_bf16_t *p) {
|
||||
return _mm512_castsi512_ps(
|
||||
_mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((const __m256i *)p)), 16));
|
||||
}
|
||||
#endif // __AVX512F__
|
||||
|
||||
#if defined(__AVX512BF16__)
|
||||
template <> inline __m512bh load(const ggml_bf16_t *p) {
|
||||
return (__m512bh)_mm512_loadu_ps((const float *)p);
|
||||
}
|
||||
template <> inline __m256bh load(const ggml_bf16_t *p) {
|
||||
return (__m256bh)_mm256_loadu_ps((const float *)p);
|
||||
}
|
||||
template <> inline __m512bh load(const float *p) {
|
||||
return _mm512_cvtne2ps_pbh(_mm512_loadu_ps(p + 16), _mm512_loadu_ps(p));
|
||||
}
|
||||
template <> inline __m256bh load(const float *p) {
|
||||
return _mm512_cvtneps_pbh(_mm512_loadu_ps(p));
|
||||
}
|
||||
#endif
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
// CONSTANTS
|
||||
|
||||
@ -290,170 +252,199 @@ static const __m128i iq4nlt = _mm_loadu_si128((const __m128i *) kvalues_iq4nl);
|
||||
////////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
// FLOATING POINT MATRIX MULTIPLICATION
|
||||
|
||||
template <int M>
|
||||
static inline int64_t BLOCK_SIZE(size_t m) {
|
||||
const int64_t NB_BLOC_M = (m + M - 1) / M;
|
||||
return (m % NB_BLOC_M == 0) ? m / NB_BLOC_M : (m / NB_BLOC_M) + 1;
|
||||
}
|
||||
|
||||
static constexpr inline int64_t BLOC_POS(int64_t ib, int64_t ibN, int64_t bloc_size) {
|
||||
return ib < ibN ? ib * bloc_size : ibN * bloc_size + (ib - ibN) * (bloc_size - 1);
|
||||
}
|
||||
|
||||
template <int KN, typename D, typename V, typename TA, typename TB, typename TC>
|
||||
class tinyBLAS {
|
||||
public:
|
||||
tinyBLAS(const ggml_compute_params * params, int64_t k,
|
||||
tinyBLAS(int64_t k,
|
||||
const TA *A, int64_t lda,
|
||||
const TB *B, int64_t ldb,
|
||||
TC *C, int64_t ldc)
|
||||
: params(params), A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc) {
|
||||
TC *C, int64_t ldc,
|
||||
int ith, int nth)
|
||||
: A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
|
||||
}
|
||||
|
||||
bool matmul(int64_t m, int64_t n) {
|
||||
if (k % KN != 0)
|
||||
return false;
|
||||
// compute RM for only need tile with size RM&RM-1
|
||||
#if VECTOR_REGISTERS == 32
|
||||
if (m % 16 == 0 && (m/16 >= params->nth)) {
|
||||
const int64_t SIZE_N = BLOCK_SIZE<6>(n);
|
||||
mnpack<4, 6, 4>(m, n, SIZE_N, 12);
|
||||
return true;
|
||||
}
|
||||
if (m % 8 == 0 ) {
|
||||
const int64_t SIZE_N = BLOCK_SIZE<6>(n);
|
||||
mnpack<4, 6, 2>(m, n, SIZE_N, 12);
|
||||
return true;
|
||||
}
|
||||
if (m % 4 == 0) {
|
||||
const int64_t SIZE_N = BLOCK_SIZE<6>(n);
|
||||
mnpack<4, 6, 1>(m, n, SIZE_N, 12);
|
||||
return true;
|
||||
}
|
||||
#else // VECTOR_REGISTERS == 16
|
||||
if (m % 16 == 0 && (m/16 >= params->nth)) {
|
||||
const int64_t SIZE_N = BLOCK_SIZE<3>(n);
|
||||
mnpack<4, 3, 4>(m, n, SIZE_N, 24);
|
||||
return true;
|
||||
}
|
||||
if (m % 8 == 0 ) {
|
||||
const int64_t SIZE_N = BLOCK_SIZE<3>(n);
|
||||
mnpack<4, 3, 2>(m, n, SIZE_N, 24);
|
||||
return true;
|
||||
}
|
||||
if (m % 4 == 0) {
|
||||
const int64_t SIZE_N = BLOCK_SIZE<3>(n);
|
||||
mnpack<4, 3, 1>(m, n, SIZE_N, 24);
|
||||
return true;
|
||||
}
|
||||
#endif
|
||||
return false;
|
||||
void matmul(int64_t m, int64_t n) {
|
||||
mnpack(0, m, 0, n);
|
||||
}
|
||||
|
||||
private:
|
||||
template <int RM, int RN, int BM>
|
||||
inline void mnpack(int64_t m, int64_t n, int64_t SIZE_N, int64_t BN) {
|
||||
if (SIZE_N == RN) {
|
||||
return gemm<RM, RN, BM>(m, n, BN);
|
||||
}
|
||||
if constexpr (RN > 1) {
|
||||
return mnpack<RM, RN-1, BM>(m, n, SIZE_N, BN);
|
||||
} else {
|
||||
GGML_LOG_ERROR("mnpack<%d, %d> bloc size not supported\n", RM, (int)SIZE_N);
|
||||
GGML_ASSERT(false); // we have miss something.
|
||||
NOINLINE void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
|
||||
int64_t mc, nc, mp, np;
|
||||
switch ((MIN(m - m0, 5) << 4) | MIN(n - n0, 5)) {
|
||||
#if VECTOR_REGISTERS == 32
|
||||
case 0x55:
|
||||
mc = 5;
|
||||
nc = 5;
|
||||
gemm<5, 5>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x45:
|
||||
mc = 4;
|
||||
nc = 5;
|
||||
gemm<4, 5>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x54:
|
||||
mc = 5;
|
||||
nc = 4;
|
||||
gemm<5, 4>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x44:
|
||||
mc = 4;
|
||||
nc = 4;
|
||||
gemm<4, 4>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x53:
|
||||
mc = 5;
|
||||
nc = 3;
|
||||
gemm<5, 3>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x35:
|
||||
mc = 3;
|
||||
nc = 5;
|
||||
gemm<3, 5>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x43:
|
||||
mc = 4;
|
||||
nc = 3;
|
||||
gemm<4, 3>(m0, m, n0, n);
|
||||
break;
|
||||
#else
|
||||
case 0x55:
|
||||
case 0x54:
|
||||
case 0x53:
|
||||
case 0x45:
|
||||
case 0x44:
|
||||
case 0x43:
|
||||
mc = 4;
|
||||
nc = 3;
|
||||
gemm<4, 3>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x35:
|
||||
#endif
|
||||
case 0x34:
|
||||
mc = 3;
|
||||
nc = 4;
|
||||
gemm<3, 4>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x52:
|
||||
mc = 5;
|
||||
nc = 2;
|
||||
gemm<5, 2>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x33:
|
||||
mc = 3;
|
||||
nc = 3;
|
||||
gemm<3, 3>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x25:
|
||||
mc = 2;
|
||||
nc = 5;
|
||||
gemm<2, 5>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x42:
|
||||
mc = 4;
|
||||
nc = 2;
|
||||
gemm<4, 2>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x24:
|
||||
mc = 2;
|
||||
nc = 4;
|
||||
gemm<2, 4>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x32:
|
||||
mc = 3;
|
||||
nc = 2;
|
||||
gemm<3, 2>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x23:
|
||||
mc = 2;
|
||||
nc = 3;
|
||||
gemm<2, 3>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x51:
|
||||
mc = 5;
|
||||
nc = 1;
|
||||
gemm<5, 1>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x41:
|
||||
mc = 4;
|
||||
nc = 1;
|
||||
gemm<4, 1>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x22:
|
||||
mc = 2;
|
||||
nc = 2;
|
||||
gemm<2, 2>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x15:
|
||||
mc = 1;
|
||||
nc = 5;
|
||||
gemm<1, 5>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x14:
|
||||
mc = 1;
|
||||
nc = 4;
|
||||
gemm<1, 4>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x31:
|
||||
mc = 3;
|
||||
nc = 1;
|
||||
gemm<3, 1>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x13:
|
||||
mc = 1;
|
||||
nc = 3;
|
||||
gemm<1, 3>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x21:
|
||||
mc = 2;
|
||||
nc = 1;
|
||||
gemm<2, 1>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x12:
|
||||
mc = 1;
|
||||
nc = 2;
|
||||
gemm<1, 2>(m0, m, n0, n);
|
||||
break;
|
||||
case 0x11:
|
||||
mc = 1;
|
||||
nc = 1;
|
||||
gemm<1, 1>(m0, m, n0, n);
|
||||
break;
|
||||
default:
|
||||
return;
|
||||
}
|
||||
mp = m0 + (m - m0) / mc * mc;
|
||||
np = n0 + (n - n0) / nc * nc;
|
||||
mnpack(mp, m, n0, np);
|
||||
mnpack(m0, m, np, n);
|
||||
}
|
||||
|
||||
template <int RM, int RN>
|
||||
inline void gemm_bloc(int64_t ii, int64_t jj) {
|
||||
D Cv[RN][RM] = {};
|
||||
for (int64_t l = 0; l < k; l += KN) {
|
||||
// help compiler for op order.
|
||||
if constexpr (RM <= RN) {
|
||||
V Av[RM];
|
||||
for (int64_t i = 0; i < RM; ++i) {
|
||||
Av[i] = load<V>(A + lda * (ii + i) + l);
|
||||
}
|
||||
for (int64_t j = 0; j < RN; ++j) {
|
||||
V Bv = load<V>(B + ldb * (jj + j) + l);
|
||||
for (int64_t i = 0; i < RM; ++i) {
|
||||
Cv[j][i] = madd(Av[i], Bv, Cv[j][i]);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
V Bv[RN];
|
||||
for (int64_t j = 0; j < RN; ++j) {
|
||||
Bv[j] = load<V>(B + ldb * (jj + j) + l);
|
||||
}
|
||||
for (int64_t i = 0; i < RM; ++i) {
|
||||
V Av = load<V>(A + lda * (ii + i) + l);
|
||||
for (int64_t j = 0; j < RN; ++j) {
|
||||
Cv[j][i] = madd(Av, Bv[j], Cv[j][i]);
|
||||
}
|
||||
}
|
||||
}
|
||||
NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
|
||||
int64_t ytiles = (m - m0) / RM;
|
||||
int64_t xtiles = (n - n0) / RN;
|
||||
int64_t tiles = xtiles * ytiles;
|
||||
int64_t duty = (tiles + nth - 1) / nth;
|
||||
int64_t start = duty * ith;
|
||||
int64_t end = start + duty;
|
||||
if (end > tiles)
|
||||
end = tiles;
|
||||
for (int64_t job = start; job < end; ++job) {
|
||||
int64_t ii = m0 + job / xtiles * RM;
|
||||
int64_t jj = n0 + job % xtiles * RN;
|
||||
D Cv[RN][RM] = {};
|
||||
for (int64_t l = 0; l < k; l += KN)
|
||||
for (int64_t j = 0; j < RN; ++j)
|
||||
for (int64_t i = 0; i < RM; ++i)
|
||||
Cv[j][i] = madd(load<V>(A + lda * (ii + i) + l),
|
||||
load<V>(B + ldb * (jj + j) + l),
|
||||
Cv[j][i]);
|
||||
for (int64_t j = 0; j < RN; ++j)
|
||||
for (int64_t i = 0; i < RM; ++i)
|
||||
C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
|
||||
}
|
||||
for (int64_t j = 0; j < RN; ++j)
|
||||
for (int64_t i = 0; i < RM; ++i)
|
||||
C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
|
||||
}
|
||||
|
||||
template <int RM, int RN, int BM>
|
||||
NOINLINE void gemm(int64_t m, int64_t n, int64_t BN) {
|
||||
static std::atomic<int64_t> current_chunk;
|
||||
|
||||
GGML_ASSERT(m % (RM * BM) == 0);
|
||||
const int64_t ytiles = m / (RM * BM);
|
||||
const int64_t xtiles = (n + RN -1) / RN;
|
||||
const int64_t jj_RN = (xtiles - (xtiles * RN - n));
|
||||
|
||||
// "round" bloc_size to "nearest" BN
|
||||
const int64_t NB_BN = xtiles < BN ? 1 : (xtiles + BN / 2) / BN;
|
||||
const int64_t SIZE_BN = xtiles % NB_BN == 0 ? xtiles / NB_BN : xtiles / NB_BN + 1;
|
||||
const int64_t jj_BN = (NB_BN - (NB_BN * SIZE_BN - xtiles));
|
||||
const int64_t nb_job = ytiles * NB_BN;
|
||||
|
||||
if (params->ith == 0) {
|
||||
GGML_ASSERT( jj_BN * SIZE_BN + (NB_BN - jj_BN) * (SIZE_BN - 1) == xtiles);
|
||||
// Every thread starts at ith, so the first unprocessed chunk is nth. This save a bit of coordination right at the start.
|
||||
std::atomic_store_explicit(¤t_chunk, (int64_t)params->nth, std::memory_order_relaxed);
|
||||
}
|
||||
|
||||
ggml_barrier(params->threadpool);
|
||||
|
||||
int64_t job = params->ith;
|
||||
while (job < nb_job) {
|
||||
const int64_t ii = (job % ytiles) * RM * BM;
|
||||
const int64_t jb = job / ytiles;
|
||||
const int64_t jr0 = BLOC_POS(jb , jj_BN, SIZE_BN);
|
||||
const int64_t jrN = BLOC_POS(jb+1, jj_BN, SIZE_BN);
|
||||
|
||||
const int64_t jj0 = BLOC_POS(jr0, jj_RN, RN);
|
||||
const int64_t jj2 = BLOC_POS(jrN, jj_RN, RN);
|
||||
const int64_t jj1 = jj2 < jj_RN * RN ? jj2 : jj_RN * RN;
|
||||
|
||||
for (int64_t bi = 0; bi < BM * RM; bi += RM) {
|
||||
int64_t jj = jj0;
|
||||
for (; jj < jj1; jj += RN) {
|
||||
gemm_bloc<RM, RN>(ii + bi, jj);
|
||||
}
|
||||
if constexpr (RN > 1) {
|
||||
for (; jj < jj2; jj += RN - 1) {
|
||||
gemm_bloc<RM, RN-1>(ii + bi, jj);
|
||||
}
|
||||
}
|
||||
GGML_ASSERT(jj == jj2);
|
||||
}
|
||||
|
||||
// next step.
|
||||
job = std::atomic_fetch_add_explicit(¤t_chunk, (int64_t)1, std::memory_order_relaxed);
|
||||
}
|
||||
|
||||
ggml_barrier(params->threadpool);
|
||||
return;
|
||||
}
|
||||
|
||||
const ggml_compute_params * params;
|
||||
const TA *const A;
|
||||
const TB *const B;
|
||||
TC *const C;
|
||||
@ -461,6 +452,8 @@ class tinyBLAS {
|
||||
const int64_t lda;
|
||||
const int64_t ldb;
|
||||
const int64_t ldc;
|
||||
const int ith;
|
||||
const int nth;
|
||||
};
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////////////////
|
||||
@ -1664,9 +1657,8 @@ class tinyBLAS_PPC {
|
||||
* @param Ctype is GGML data type of `C`
|
||||
* @return true if this function was able to service the matmul request
|
||||
*/
|
||||
bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64_t n, int64_t k,
|
||||
const void *A, int64_t lda, const void *B, int64_t ldb, void *C,
|
||||
int64_t ldc, int Atype, int Btype, int Ctype) {
|
||||
bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda, const void *B, int64_t ldb, void *C,
|
||||
int64_t ldc, int ith, int nth, int Atype, int Btype, int Ctype) {
|
||||
|
||||
assert(m >= 0);
|
||||
assert(n >= 0);
|
||||
@ -1674,8 +1666,8 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
assert(lda >= k);
|
||||
assert(ldb >= k);
|
||||
assert(ldc >= m);
|
||||
assert(params->nth > 0);
|
||||
assert(params->ith < params->nth);
|
||||
assert(nth > 0);
|
||||
assert(ith < nth);
|
||||
|
||||
// only enable sgemm for prompt processing
|
||||
if (n < 2)
|
||||
@ -1690,25 +1682,37 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
if (Btype != GGML_TYPE_F32)
|
||||
return false;
|
||||
#if defined(__AVX512F__)
|
||||
tinyBLAS<16, __m512, __m512, float, float, float> tb{ params,
|
||||
if (k % 16)
|
||||
return false;
|
||||
tinyBLAS<16, __m512, __m512, float, float, float> tb{
|
||||
k, (const float *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif defined(__AVX__) || defined(__AVX2__)
|
||||
tinyBLAS<8, __m256, __m256, float, float, float> tb{ params,
|
||||
if (k % 8)
|
||||
return false;
|
||||
tinyBLAS<8, __m256, __m256, float, float, float> tb{
|
||||
k, (const float *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif defined(__ARM_NEON)
|
||||
if (n < 4)
|
||||
return false;
|
||||
tinyBLAS<4, float32x4_t, float32x4_t, float, float, float> tb{ params,
|
||||
if (k % 4)
|
||||
return false;
|
||||
tinyBLAS<4, float32x4_t, float32x4_t, float, float, float> tb{
|
||||
k, (const float *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif defined(__MMA__)
|
||||
if (k % 8)
|
||||
return false;
|
||||
@ -1716,7 +1720,7 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
k, (const float *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
params->ith, params->nth};
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1724,71 +1728,60 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
#endif
|
||||
}
|
||||
|
||||
case GGML_TYPE_BF16: {
|
||||
#if defined(__AVX512BF16__)
|
||||
if (Btype == GGML_TYPE_BF16) {
|
||||
tinyBLAS<32, __m512, __m512bh, ggml_bf16_t, ggml_bf16_t, float> tb{ params, k,
|
||||
(const ggml_bf16_t *)A, lda,
|
||||
(const ggml_bf16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#elif defined(__AVX512F__)
|
||||
if (Btype == GGML_TYPE_BF16) {
|
||||
tinyBLAS<16, __m512, __m512, ggml_bf16_t, ggml_bf16_t, float> tb{ params, k,
|
||||
(const ggml_bf16_t *)A, lda,
|
||||
(const ggml_bf16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#elif defined(__AVX2__)
|
||||
if (Btype == GGML_TYPE_BF16) {
|
||||
tinyBLAS<8, __m256, __m256, ggml_bf16_t, ggml_bf16_t, float> tb{ params, k,
|
||||
(const ggml_bf16_t *)A, lda,
|
||||
(const ggml_bf16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#endif
|
||||
return false;
|
||||
}
|
||||
case GGML_TYPE_F16: {
|
||||
#if defined(__AVX512F__)
|
||||
if (Btype == GGML_TYPE_F16) {
|
||||
tinyBLAS<16, __m512, __m512, ggml_fp16_t, ggml_fp16_t, float> tb{ params, k,
|
||||
(const ggml_fp16_t *)A, lda,
|
||||
(const ggml_fp16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
if (k % 16)
|
||||
return false;
|
||||
if (Btype != GGML_TYPE_F32)
|
||||
return false;
|
||||
tinyBLAS<16, __m512, __m512, ggml_fp16_t, float, float> tb{
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif (defined(__AVX__) || defined(__AVX2__)) && defined(__F16C__)
|
||||
if (Btype == GGML_TYPE_F16) {
|
||||
tinyBLAS<8, __m256, __m256, ggml_fp16_t, ggml_fp16_t, float> tb{ params, k,
|
||||
(const ggml_fp16_t *)A, lda,
|
||||
(const ggml_fp16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
if (k % 8)
|
||||
return false;
|
||||
if (Btype != GGML_TYPE_F32)
|
||||
return false;
|
||||
tinyBLAS<8, __m256, __m256, ggml_fp16_t, float, float> tb{
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && !defined(_MSC_VER)
|
||||
if (n < 8)
|
||||
return false;
|
||||
if (Btype == GGML_TYPE_F16) {
|
||||
tinyBLAS<8, float16x8_t, float16x8_t, ggml_fp16_t, ggml_fp16_t, float> tb{ params,
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const ggml_fp16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
if (k % 8)
|
||||
return false;
|
||||
if (Btype != GGML_TYPE_F16)
|
||||
return false;
|
||||
tinyBLAS<8, float16x8_t, float16x8_t, ggml_fp16_t, ggml_fp16_t, float> tb{
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const ggml_fp16_t *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif defined(__ARM_NEON) && !defined(_MSC_VER)
|
||||
if (Btype == GGML_TYPE_F32) {
|
||||
tinyBLAS<4, float32x4_t, float32x4_t, ggml_fp16_t, float, float> tb{ params,
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#endif
|
||||
if (k % 4)
|
||||
return false;
|
||||
if (Btype != GGML_TYPE_F32)
|
||||
return false;
|
||||
tinyBLAS<4, float32x4_t, float32x4_t, ggml_fp16_t, float, float> tb{
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
return false;
|
||||
#endif
|
||||
}
|
||||
|
||||
case GGML_TYPE_Q8_0: {
|
||||
@ -1799,7 +1792,7 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
k, (const block_q8_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
params->ith, params->nth};
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif defined(__ARM_FEATURE_DOTPROD)
|
||||
@ -1807,7 +1800,7 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
k, (const block_q8_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
params->ith, params->nth};
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1823,7 +1816,7 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
k, (const block_q4_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
params->ith, params->nth};
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif defined(__ARM_FEATURE_DOTPROD)
|
||||
@ -1831,7 +1824,7 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
k, (const block_q4_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
params->ith, params->nth};
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1847,7 +1840,7 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
k, (const block_q5_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
params->ith, params->nth};
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1863,7 +1856,7 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
k, (const block_iq4_nl *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
params->ith, params->nth};
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1875,7 +1868,6 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
return false;
|
||||
}
|
||||
|
||||
(void)params;
|
||||
(void)m;
|
||||
(void)n;
|
||||
(void)k;
|
||||
@ -1885,6 +1877,8 @@ bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64
|
||||
(void)ldb;
|
||||
(void)C;
|
||||
(void)ldc;
|
||||
(void)ith;
|
||||
(void)nth;
|
||||
(void)Atype;
|
||||
(void)Btype;
|
||||
(void)Ctype;
|
||||
|
||||
@ -5,8 +5,8 @@
|
||||
extern "C" {
|
||||
#endif
|
||||
|
||||
bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t, int64_t, int64_t,
|
||||
const void *, int64_t, const void *, int64_t, void *, int64_t,
|
||||
bool llamafile_sgemm(int64_t, int64_t, int64_t, const void *, int64_t,
|
||||
const void *, int64_t, void *, int64_t, int, int,
|
||||
int, int, int);
|
||||
|
||||
#ifdef __cplusplus
|
||||
|
||||
@ -126,8 +126,6 @@ connection = sqlite3.connect(input_file)
|
||||
cursor = connection.cursor()
|
||||
builds = cursor.execute("SELECT DISTINCT build_commit FROM test;").fetchall()
|
||||
|
||||
commit_short_len = len(builds[0][0])
|
||||
|
||||
try:
|
||||
repo = git.Repo(".", search_parent_directories=True)
|
||||
except git.InvalidGitRepositoryError:
|
||||
@ -140,11 +138,11 @@ def find_parent_in_data(commit: git.Commit):
|
||||
seen_hexsha8 = set()
|
||||
while heap:
|
||||
depth, current_commit = heapq.heappop(heap)
|
||||
current_hexsha8 = commit.hexsha[:commit_short_len]
|
||||
current_hexsha8 = commit.hexsha[:8]
|
||||
if (current_hexsha8,) in builds:
|
||||
return current_hexsha8
|
||||
for parent in commit.parents:
|
||||
parent_hexsha8 = parent.hexsha[:commit_short_len]
|
||||
parent_hexsha8 = parent.hexsha[:8]
|
||||
if parent_hexsha8 not in seen_hexsha8:
|
||||
seen_hexsha8.add(parent_hexsha8)
|
||||
heapq.heappush(heap, (depth + 1, parent))
|
||||
@ -158,9 +156,9 @@ def get_all_parent_hexsha8s(commit: git.Commit):
|
||||
|
||||
while unvisited:
|
||||
current_commit = unvisited.pop(0)
|
||||
visited.append(current_commit.hexsha[:commit_short_len])
|
||||
visited.append(current_commit.hexsha[:8])
|
||||
for parent in current_commit.parents:
|
||||
if parent.hexsha[:commit_short_len] not in visited:
|
||||
if parent.hexsha[:8] not in visited:
|
||||
unvisited.append(parent)
|
||||
|
||||
return visited
|
||||
@ -171,10 +169,10 @@ def get_commit_name(hexsha8):
|
||||
if repo is None:
|
||||
return hexsha8
|
||||
for h in repo.heads:
|
||||
if h.commit.hexsha[:commit_short_len] == hexsha8:
|
||||
if h.commit.hexsha[:8] == hexsha8:
|
||||
return h.name
|
||||
for t in repo.tags:
|
||||
if t.commit.hexsha[:commit_short_len] == hexsha8:
|
||||
if t.commit.hexsha[:8] == hexsha8:
|
||||
return t.name
|
||||
return hexsha8
|
||||
|
||||
@ -185,13 +183,13 @@ def get_commit_hexsha8(name):
|
||||
return None
|
||||
for h in repo.heads:
|
||||
if h.name == name:
|
||||
return h.commit.hexsha[:commit_short_len]
|
||||
return h.commit.hexsha[:8]
|
||||
for t in repo.tags:
|
||||
if t.name == name:
|
||||
return t.commit.hexsha[:commit_short_len]
|
||||
return t.commit.hexsha[:8]
|
||||
for c in repo.iter_commits("--all"):
|
||||
if c.hexsha[:commit_short_len] == name[:commit_short_len]:
|
||||
return c.hexsha[:commit_short_len]
|
||||
if c.hexsha[:8] == name[:8]:
|
||||
return c.hexsha[:8]
|
||||
return None
|
||||
|
||||
|
||||
|
||||
@ -26,7 +26,7 @@ function has_cmd {
|
||||
}
|
||||
|
||||
if has_cmd wget; then
|
||||
cmd="wget -q -c -O %s/%s %s"
|
||||
cmd="wget -q --show-progress -c -O %s/%s %s"
|
||||
elif has_cmd curl; then
|
||||
cmd="curl -C - -f --output-dir %s -o %s -L %s"
|
||||
else
|
||||
|
||||
@ -1657,7 +1657,7 @@ bool llama_token_is_control_impl(const struct llama_vocab & vocab, llama_token t
|
||||
}
|
||||
|
||||
llama_token llama_token_bos_impl(const struct llama_vocab & vocab) {
|
||||
return vocab.type != LLAMA_VOCAB_TYPE_WPM ? vocab.special_bos_id : vocab.special_cls_id;
|
||||
return vocab.special_bos_id;
|
||||
}
|
||||
|
||||
llama_token llama_token_eos_impl(const struct llama_vocab & vocab) {
|
||||
|
||||
@ -45,7 +45,7 @@ struct llama_vocab {
|
||||
id special_unk_id = 0;
|
||||
id special_sep_id = LLAMA_TOKEN_NULL;
|
||||
id special_pad_id = LLAMA_TOKEN_NULL;
|
||||
id special_cls_id = LLAMA_TOKEN_NULL; // TODO: revisit if this is really needed https://github.com/ggerganov/llama.cpp/pull/10930
|
||||
id special_cls_id = LLAMA_TOKEN_NULL;
|
||||
id special_mask_id = LLAMA_TOKEN_NULL;
|
||||
|
||||
id linefeed_id = 13;
|
||||
|
||||
Loading…
Reference in New Issue
Block a user