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36 changed files with 591 additions and 664 deletions

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@@ -79,7 +79,7 @@ jobs:
# Setup nodejs (to be used for verifying bundled index.html)
- uses: actions/setup-node@v4
with:
node-version: '22.11.0'
node-version: 22
- name: Verify bundled index.html
id: verify_server_index_html

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@@ -2083,35 +2083,35 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
[](common_params & params, int value) {
params.speculative.n_max = value;
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_DRAFT_MAX"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER}));
add_opt(common_arg(
{"--draft-min", "--draft-n-min"}, "N",
string_format("minimum number of draft tokens to use for speculative decoding (default: %d)", params.speculative.n_min),
[](common_params & params, int value) {
params.speculative.n_min = value;
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_DRAFT_MIN"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER}));
add_opt(common_arg(
{"--draft-p-split"}, "P",
string_format("speculative decoding split probability (default: %.1f)", (double)params.speculative.p_split),
[](common_params & params, const std::string & value) {
params.speculative.p_split = std::stof(value);
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE}).set_env("LLAMA_ARG_DRAFT_P_SPLIT"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE}));
add_opt(common_arg(
{"--draft-p-min"}, "P",
string_format("minimum speculative decoding probability (greedy) (default: %.1f)", (double)params.speculative.p_min),
[](common_params & params, const std::string & value) {
params.speculative.p_min = std::stof(value);
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_DRAFT_P_MIN"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
add_opt(common_arg(
{"-cd", "--ctx-size-draft"}, "N",
string_format("size of the prompt context for the draft model (default: %d, 0 = loaded from model)", params.speculative.n_ctx),
[](common_params & params, int value) {
params.speculative.n_ctx = value;
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_CTX_SIZE_DRAFT"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
add_opt(common_arg(
{"-devd", "--device-draft"}, "<dev1,dev2,..>",
"comma-separated list of devices to use for offloading the draft model (none = don't offload)\n"
@@ -2131,14 +2131,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
fprintf(stderr, "warning: consult docs/build.md for compilation instructions\n");
}
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_N_GPU_LAYERS_DRAFT"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
add_opt(common_arg(
{"-md", "--model-draft"}, "FNAME",
"draft model for speculative decoding (default: unused)",
[](common_params & params, const std::string & value) {
params.speculative.model = value;
}
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_MODEL_DRAFT"));
).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER}));
return ctx_arg;
}

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@@ -20,12 +20,7 @@ else()
add_subdirectory(batched)
add_subdirectory(embedding)
add_subdirectory(eval-callback)
if (NOT WIN32)
# disabled on Windows because it uses internal functions not exported with LLAMA_API
add_subdirectory(gbnf-validator)
endif()
add_subdirectory(gbnf-validator)
add_subdirectory(gguf-hash)
add_subdirectory(gguf-split)
add_subdirectory(gguf)
@@ -56,10 +51,7 @@ else()
add_subdirectory(convert-llama2c-to-ggml)
add_subdirectory(cvector-generator)
add_subdirectory(export-lora)
if (NOT WIN32)
# disabled on Windows because it uses internal functions not exported with LLAMA_API
add_subdirectory(quantize-stats)
endif()
add_subdirectory(quantize-stats)
add_subdirectory(llava)
if (GGML_RPC)
add_subdirectory(rpc)

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@@ -287,7 +287,7 @@ struct split_strategy {
}
void print_info() {
printf("n_split: %zu\n", ctx_outs.size());
printf("n_split: %ld\n", ctx_outs.size());
int i_split = 0;
for (auto & ctx_out : ctx_outs) {
// re-calculate the real gguf size for each split (= metadata size + total size of all tensors)
@@ -297,7 +297,7 @@ struct split_strategy {
total_size += ggml_nbytes(t);
}
total_size = total_size / 1000 / 1000; // convert to megabytes
printf("split %05d: n_tensors = %d, total_size = %zuM\n", i_split + 1, gguf_get_n_tensors(ctx_out), total_size);
printf("split %05d: n_tensors = %d, total_size = %ldM\n", i_split + 1, gguf_get_n_tensors(ctx_out), total_size);
i_split++;
}
}

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@@ -1521,7 +1521,7 @@ int main(int argc, char ** argv) {
for (const auto & inst : params_instances) {
params_idx++;
if (params.progress) {
fprintf(stderr, "llama-bench: benchmark %d/%zu: starting\n", params_idx, params_count);
fprintf(stderr, "llama-bench: benchmark %d/%ld: starting\n", params_idx, params_count);
}
// keep the same model between tests when possible
if (!lmodel || !prev_inst || !inst.equal_mparams(*prev_inst)) {
@@ -1573,14 +1573,14 @@ int main(int argc, char ** argv) {
// warmup run
if (t.n_prompt > 0) {
if (params.progress) {
fprintf(stderr, "llama-bench: benchmark %d/%zu: warmup prompt run\n", params_idx, params_count);
fprintf(stderr, "llama-bench: benchmark %d/%ld: warmup prompt run\n", params_idx, params_count);
}
//test_prompt(ctx, std::min(t.n_batch, std::min(t.n_prompt, 32)), 0, t.n_batch, t.n_threads);
test_prompt(ctx, t.n_prompt, t.n_batch, t.n_threads);
}
if (t.n_gen > 0) {
if (params.progress) {
fprintf(stderr, "llama-bench: benchmark %d/%zu: warmup generation run\n", params_idx, params_count);
fprintf(stderr, "llama-bench: benchmark %d/%ld: warmup generation run\n", params_idx, params_count);
}
test_gen(ctx, 1, t.n_threads);
}
@@ -1592,14 +1592,14 @@ int main(int argc, char ** argv) {
if (t.n_prompt > 0) {
if (params.progress) {
fprintf(stderr, "llama-bench: benchmark %d/%zu: prompt run %d/%d\n", params_idx, params_count,
fprintf(stderr, "llama-bench: benchmark %d/%ld: prompt run %d/%d\n", params_idx, params_count,
i + 1, params.reps);
}
test_prompt(ctx, t.n_prompt, t.n_batch, t.n_threads);
}
if (t.n_gen > 0) {
if (params.progress) {
fprintf(stderr, "llama-bench: benchmark %d/%zu: generation run %d/%d\n", params_idx, params_count,
fprintf(stderr, "llama-bench: benchmark %d/%ld: generation run %d/%d\n", params_idx, params_count,
i + 1, params.reps);
}
test_gen(ctx, t.n_gen, t.n_threads);

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@@ -81,7 +81,7 @@ Several quantization methods are supported. They differ in the resulting model d
- [#4930 - imatrix for all k-quants](https://github.com/ggerganov/llama.cpp/pull/4930)
- [#4951 - imatrix on the GPU](https://github.com/ggerganov/llama.cpp/pull/4957)
- [#4969 - imatrix for legacy quants](https://github.com/ggerganov/llama.cpp/pull/4969)
- [#4996 - k-quants tuning](https://github.com/ggerganov/llama.cpp/pull/4996)
- [#4996 - k-qunats tuning](https://github.com/ggerganov/llama.cpp/pull/4996)
- [#5060 - Q3_K_XS](https://github.com/ggerganov/llama.cpp/pull/5060)
- [#5196 - 3-bit i-quants](https://github.com/ggerganov/llama.cpp/pull/5196)
- [quantization tuning](https://github.com/ggerganov/llama.cpp/pull/5320), [another one](https://github.com/ggerganov/llama.cpp/pull/5334), and [another one](https://github.com/ggerganov/llama.cpp/pull/5361)

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@@ -143,7 +143,7 @@ int main(int argc, char ** argv) {
std::vector<chunk> file_chunk = chunk_file(context_file, params.chunk_size, params.chunk_separator);
chunks.insert(chunks.end(), file_chunk.begin(), file_chunk.end());
}
LOG_INF("Number of chunks: %zu\n", chunks.size());
LOG_INF("Number of chunks: %ld\n", chunks.size());
llama_backend_init();
llama_numa_init(params.numa);

View File

@@ -303,23 +303,23 @@ mkdir llama-client
cd llama-client
```
Create an index.js file and put this inside:
Create a index.js file and put this inside:
```javascript
const prompt = "Building a website can be done in 10 simple steps:"
const prompt = `Building a website can be done in 10 simple steps:`;
async function test() {
async function Test() {
let response = await fetch("http://127.0.0.1:8080/completion", {
method: "POST",
method: 'POST',
body: JSON.stringify({
prompt,
n_predict: 64,
n_predict: 512,
})
})
console.log((await response.json()).content)
}
test()
Test()
```
And run it:
@@ -381,7 +381,7 @@ Multiple prompts are also supported. In this case, the completion result will be
`n_keep`: Specify the number of tokens from the prompt to retain when the context size is exceeded and tokens need to be discarded. The number excludes the BOS token.
By default, this value is set to `0`, meaning no tokens are kept. Use `-1` to retain all tokens from the prompt.
`stream`: Allows receiving each predicted token in real-time instead of waiting for the completion to finish (uses a different response format). To enable this, set to `true`.
`stream`: It allows receiving each predicted token in real-time instead of waiting for the completion to finish. To enable this, set to `true`.
`stop`: Specify a JSON array of stopping strings.
These words will not be included in the completion, so make sure to add them to the prompt for the next iteration. Default: `[]`
@@ -442,11 +442,11 @@ These words will not be included in the completion, so make sure to add them to
`samplers`: The order the samplers should be applied in. An array of strings representing sampler type names. If a sampler is not set, it will not be used. If a sampler is specified more than once, it will be applied multiple times. Default: `["dry", "top_k", "typ_p", "top_p", "min_p", "xtc", "temperature"]` - these are all the available values.
`timings_per_token`: Include prompt processing and text generation speed information in each response. Default: `false`
`timings_per_token`: Include prompt processing and text generation speed information in each response. Default: `false`
**Response format**
- Note: In streaming mode (`stream`), only `content` 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.
- Note: When using streaming mode (`stream`), only `content` and `stop` will be returned until end of completion.
- `completion_probabilities`: An array of token probabilities for each completion. The array's length is `n_predict`. Each item in the array has the following structure:

File diff suppressed because one or more lines are too long

View File

@@ -333,7 +333,7 @@ static std::string llama_get_chat_template(const struct llama_model * model) {
if (res < 2) {
return "";
} else {
std::vector<char> model_template(res + 1, 0);
std::vector<char> model_template(res, 0);
llama_model_meta_val_str(model, template_key.c_str(), model_template.data(), model_template.size());
return std::string(model_template.data(), model_template.size() - 1);
}

View File

@@ -15,7 +15,7 @@
<!-- sidebar -->
<div class="drawer-side h-screen lg:h-screen z-50 lg:max-w-64">
<label for="toggle-drawer" aria-label="close sidebar" class="drawer-overlay"></label>
<div class="flex flex-col bg-base-200 min-h-full max-w-64 py-4 px-4">
<div class="flex flex-col bg-base-200 min-h-full max-w-[calc(100vw-2em)] py-4 px-4">
<div class="flex flex-row items-center justify-between mb-4 mt-4">
<h2 class="font-bold ml-4">Conversations</h2>
@@ -120,25 +120,51 @@
{{ messages.length === 0 ? 'Send a message to start' : '' }}
</div>
<div v-for="msg in messages" class="group">
<message-bubble
:config="config"
:msg="msg"
:key="msg.id"
:is-generating="isGenerating"
:edit-user-msg-and-regenerate="editUserMsgAndRegenerate"
:regenerate-msg="regenerateMsg"></message-bubble>
<div :class="{
'chat': true,
'chat-start': msg.role !== 'user',
'chat-end': msg.role === 'user',
}">
<div :class="{
'chat-bubble markdown': true,
'chat-bubble-base-300': msg.role !== 'user',
}">
<!-- textarea for editing message -->
<template v-if="editingMsg && editingMsg.id === msg.id">
<textarea
class="textarea textarea-bordered bg-base-100 text-base-content w-[calc(90vw-8em)] lg:w-96"
v-model="msg.content"></textarea>
<br/>
<button class="btn btn-ghost mt-2 mr-2" @click="editingMsg = null">Cancel</button>
<button class="btn mt-2" @click="editUserMsgAndRegenerate(msg)">Submit</button>
</template>
<!-- render message as markdown -->
<vue-markdown v-else :source="msg.content" />
</div>
</div>
<!-- actions for each message -->
<div :class="{'text-right': msg.role === 'user'}" class="mx-4 mt-2 mb-2">
<!-- user message -->
<button v-if="msg.role === 'user'" class="badge btn-mini show-on-hover" @click="editingMsg = msg" :disabled="isGenerating">
✍️ Edit
</button>
<!-- assistant message -->
<button v-if="msg.role === 'assistant'" class="badge btn-mini show-on-hover mr-2" @click="regenerateMsg(msg)" :disabled="isGenerating">
🔄 Regenerate
</button>
<button v-if="msg.role === 'assistant'" class="badge btn-mini show-on-hover mr-2" @click="copyMsg(msg)" :disabled="isGenerating">
📋 Copy
</button>
</div>
</div>
<!-- pending (ongoing) assistant message -->
<div id="pending-msg" class="group">
<message-bubble
v-if="pendingMsg"
:config="config"
:msg="pendingMsg"
:key="pendingMsg.id"
:is-generating="isGenerating"
:edit-user-msg-and-regenerate="() => {}"
:regenerate-msg="() => {}"></message-bubble>
<div id="pending-msg" class="chat chat-start">
<div v-if="pendingMsg" class="chat-bubble markdown chat-bubble-base-300">
<span v-if="!pendingMsg.content" class="loading loading-dots loading-md"></span>
<vue-markdown v-else :source="pendingMsg.content" />
</div>
</div>
</div>
@@ -201,10 +227,6 @@
<details class="collapse collapse-arrow bg-base-200 mb-2 overflow-visible">
<summary class="collapse-title font-bold">Advanced config</summary>
<div class="collapse-content">
<div class="flex flex-row items-center mb-2">
<input type="checkbox" class="checkbox" v-model="config.showTokensPerSecond" />
<span class="ml-4">Show tokens per second</span>
</div>
<label class="form-control mb-2">
<!-- Custom parameters input -->
<div class="label inline">Custom JSON config (For more info, refer to <a class="underline" href="https://github.com/ggerganov/llama.cpp/blob/master/examples/server/README.md" target="_blank" rel="noopener noreferrer">server documentation</a>)</div>
@@ -225,66 +247,6 @@
</div>
<!-- Template to be used as message bubble -->
<template id="message-bubble">
<div :class="{
'chat': true,
'chat-start': msg.role !== 'user',
'chat-end': msg.role === 'user',
}">
<div :class="{
'chat-bubble markdown': true,
'chat-bubble-base-300': msg.role !== 'user',
}">
<!-- textarea for editing message -->
<template v-if="editingContent !== null">
<textarea
class="textarea textarea-bordered bg-base-100 text-base-content w-[calc(90vw-8em)] lg:w-96"
v-model="editingContent"></textarea>
<br/>
<button class="btn btn-ghost mt-2 mr-2" @click="editingContent = null">Cancel</button>
<button class="btn mt-2" @click="editMsg()">Submit</button>
</template>
<template v-else>
<!-- show loading dots for pending message -->
<span v-if="msg.content === null" class="loading loading-dots loading-md"></span>
<!-- render message as markdown -->
<vue-markdown v-else :source="msg.content"></vue-markdown>
<!-- render timings if enabled -->
<div class="dropdown dropdown-hover dropdown-top mt-2" v-if="timings && config.showTokensPerSecond">
<div tabindex="0" role="button" class="cursor-pointer font-semibold text-sm opacity-60">Speed: {{ timings.predicted_per_second.toFixed(1) }} t/s</div>
<div class="dropdown-content bg-base-100 z-10 w-64 p-2 shadow mt-4">
<b>Prompt</b><br/>
- Tokens: {{ timings.prompt_n }}<br/>
- Time: {{ timings.prompt_ms }} ms<br/>
- Speed: {{ timings.prompt_per_second.toFixed(1) }} t/s<br/>
<b>Generation</b><br/>
- Tokens: {{ timings.predicted_n }}<br/>
- Time: {{ timings.predicted_ms }} ms<br/>
- Speed: {{ timings.predicted_per_second.toFixed(1) }} t/s<br/>
</div>
</div>
</template>
</div>
</div>
<!-- actions for each message -->
<div :class="{'text-right': msg.role === 'user', 'opacity-0': isGenerating}" class="mx-4 mt-2 mb-2">
<!-- user message -->
<button v-if="msg.role === 'user'" class="badge btn-mini show-on-hover" @click="editingContent = msg.content" :disabled="isGenerating">
✍️ Edit
</button>
<!-- assistant message -->
<button v-if="msg.role === 'assistant'" class="badge btn-mini show-on-hover mr-2" @click="regenerateMsg(msg)" :disabled="isGenerating">
🔄 Regenerate
</button>
<button v-if="msg.role === 'assistant'" class="badge btn-mini show-on-hover mr-2" @click="copyMsg()" :disabled="isGenerating">
📋 Copy
</button>
</div>
</template>
<!-- Template to be used by settings modal -->
<template id="settings-modal-short-input">
<label class="input input-bordered join-item grow flex items-center gap-2 mb-2">

View File

@@ -13,7 +13,6 @@
"markdown-it": "^14.1.0",
"postcss": "^8.4.49",
"tailwindcss": "^3.4.15",
"textlinestream": "^1.1.1",
"vite-plugin-singlefile": "^2.0.3",
"vue": "^3.5.13"
},
@@ -2678,12 +2677,6 @@
"node": ">=14.0.0"
}
},
"node_modules/textlinestream": {
"version": "1.1.1",
"resolved": "https://registry.npmjs.org/textlinestream/-/textlinestream-1.1.1.tgz",
"integrity": "sha512-iBHbi7BQxrFmwZUQJsT0SjNzlLLsXhvW/kg7EyOMVMBIrlnj/qYofwo1LVLZi+3GbUEo96Iu2eqToI2+lZoAEQ==",
"license": "MIT"
},
"node_modules/uc.micro": {
"version": "2.1.0",
"resolved": "https://registry.npmjs.org/uc.micro/-/uc.micro-2.1.0.tgz",

View File

@@ -17,7 +17,6 @@
"markdown-it": "^14.1.0",
"postcss": "^8.4.49",
"tailwindcss": "^3.4.15",
"textlinestream": "^1.1.1",
"vite-plugin-singlefile": "^2.0.3",
"vue": "^3.5.13"
}

View File

@@ -0,0 +1,225 @@
const paramDefaults = {
stream: true,
temperature: 0.2,
};
let generation_settings = null;
export class CompletionError extends Error {
constructor(message, name, data) {
super(message);
this.name = name;
}
};
// Completes the prompt as a generator. Recommended for most use cases.
//
// Example:
//
// import { llama } from '/completion.js'
//
// const request = llama("Tell me a joke", {n_predict: 800})
// for await (const chunk of request) {
// document.write(chunk.data.content)
// }
//
export async function* llama(prompt, params = {}, config = {}) {
let controller = config.controller;
const api_url = config.api_url?.replace(/\/+$/, '') || "";
if (!controller) {
controller = new AbortController();
}
const completionParams = { ...paramDefaults, ...params, prompt };
const response = await fetch(`${api_url}${config.endpoint || '/completion'}`, {
method: 'POST',
body: JSON.stringify(completionParams),
headers: {
'Connection': 'keep-alive',
'Content-Type': 'application/json',
'Accept': 'text/event-stream',
...(params.api_key ? {'Authorization': `Bearer ${params.api_key}`} : {})
},
signal: controller.signal,
});
const status = response.status;
if (status !== 200) {
try {
const body = await response.json();
if (body && body.error && body.error.message) {
throw new CompletionError(body.error.message, 'ServerError');
}
} catch (err) {
throw new CompletionError(err.message, 'ServerError');
}
}
const reader = response.body.getReader();
const decoder = new TextDecoder();
let content = "";
let leftover = ""; // Buffer for partially read lines
try {
let cont = true;
while (cont) {
const result = await reader.read();
if (result.done) {
break;
}
// Add any leftover data to the current chunk of data
const text = leftover + decoder.decode(result.value);
// Check if the last character is a line break
const endsWithLineBreak = text.endsWith('\n');
// Split the text into lines
let lines = text.split('\n');
// If the text doesn't end with a line break, then the last line is incomplete
// Store it in leftover to be added to the next chunk of data
if (!endsWithLineBreak) {
leftover = lines.pop();
} else {
leftover = ""; // Reset leftover if we have a line break at the end
}
// Parse all sse events and add them to result
const regex = /^(\S+):\s(.*)$/gm;
for (const line of lines) {
const match = regex.exec(line);
if (match) {
result[match[1]] = match[2];
if (result.data === '[DONE]') {
cont = false;
break;
}
// since we know this is llama.cpp, let's just decode the json in data
if (result.data) {
result.data = JSON.parse(result.data);
content += result.data.content;
// yield
yield result;
// if we got a stop token from server, we will break here
if (result.data.stop) {
if (result.data.generation_settings) {
generation_settings = result.data.generation_settings;
}
cont = false;
break;
}
}
if (result.error) {
try {
result.error = JSON.parse(result.error);
if (result.error.message.includes('slot unavailable')) {
// Throw an error to be caught by upstream callers
throw new Error('slot unavailable');
} else {
console.error(`llama.cpp error [${result.error.code} - ${result.error.type}]: ${result.error.message}`);
}
} catch(e) {
console.error(`llama.cpp error ${result.error}`)
}
}
}
}
}
} catch (e) {
if (e.name !== 'AbortError') {
console.error("llama error: ", e);
}
throw e;
}
finally {
controller.abort();
}
return content;
}
// Call llama, return an event target that you can subscribe to
//
// Example:
//
// import { llamaEventTarget } from '/completion.js'
//
// const conn = llamaEventTarget(prompt)
// conn.addEventListener("message", (chunk) => {
// document.write(chunk.detail.content)
// })
//
export const llamaEventTarget = (prompt, params = {}, config = {}) => {
const eventTarget = new EventTarget();
(async () => {
let content = "";
for await (const chunk of llama(prompt, params, config)) {
if (chunk.data) {
content += chunk.data.content;
eventTarget.dispatchEvent(new CustomEvent("message", { detail: chunk.data }));
}
if (chunk.data.generation_settings) {
eventTarget.dispatchEvent(new CustomEvent("generation_settings", { detail: chunk.data.generation_settings }));
}
if (chunk.data.timings) {
eventTarget.dispatchEvent(new CustomEvent("timings", { detail: chunk.data.timings }));
}
}
eventTarget.dispatchEvent(new CustomEvent("done", { detail: { content } }));
})();
return eventTarget;
}
// Call llama, return a promise that resolves to the completed text. This does not support streaming
//
// Example:
//
// llamaPromise(prompt).then((content) => {
// document.write(content)
// })
//
// or
//
// const content = await llamaPromise(prompt)
// document.write(content)
//
export const llamaPromise = (prompt, params = {}, config = {}) => {
return new Promise(async (resolve, reject) => {
let content = "";
try {
for await (const chunk of llama(prompt, params, config)) {
content += chunk.data.content;
}
resolve(content);
} catch (error) {
reject(error);
}
});
};
/**
* (deprecated)
*/
export const llamaComplete = async (params, controller, callback) => {
for await (const chunk of llama(params.prompt, params, { controller })) {
callback(chunk);
}
}
// Get the model info from the server. This is useful for getting the context window and so on.
export const llamaModelInfo = async (config = {}) => {
if (!generation_settings) {
const api_url = config.api_url?.replace(/\/+$/, '') || "";
const props = await fetch(`${api_url}/props`).then(r => r.json());
generation_settings = props.default_generation_settings;
}
return generation_settings;
}

View File

@@ -1,25 +1,21 @@
import './styles.css';
import { createApp, defineComponent, shallowRef, computed, h } from 'vue/dist/vue.esm-bundler.js';
import { llama } from './completion.js';
import MarkdownIt from 'markdown-it';
import TextLineStream from 'textlinestream';
const isDev = import.meta.env.MODE === 'development';
// utility functions
const isString = (x) => !!x.toLowerCase;
const isBoolean = (x) => x === true || x === false;
const isNumeric = (n) => !isString(n) && !isNaN(n) && !isBoolean(n);
const isNumeric = (n) => !isString(n) && !isNaN(n);
const escapeAttr = (str) => str.replace(/>/g, '&gt;').replace(/"/g, '&quot;');
const copyStr = (str) => navigator.clipboard.writeText(str);
// constants
const BASE_URL = localStorage.getItem('base') // for debugging
|| (new URL('.', document.baseURI).href).toString().replace(/\/$/, ''); // for production
|| (new URL('.', document.baseURI).href).toString(); // for production
const CONFIG_DEFAULT = {
// Note: in order not to introduce breaking changes, please keep the same data type (number, string, etc) if you want to change the default value. Do not use null or undefined for default value.
apiKey: '',
systemMessage: 'You are a helpful assistant.',
showTokensPerSecond: false,
// make sure these default values are in sync with `common.h`
samplers: 'dkypmxt',
temperature: 0.8,
@@ -105,48 +101,6 @@ const SettingsModalShortInput = defineComponent({
},
});
// message bubble component
const MessageBubble = defineComponent({
components: {
VueMarkdown
},
template: document.getElementById('message-bubble').innerHTML,
props: {
config: Object,
msg: Object,
isGenerating: Boolean,
editUserMsgAndRegenerate: Function,
regenerateMsg: Function,
},
data() {
return {
editingContent: null,
};
},
computed: {
timings() {
if (!this.msg.timings) return null;
return {
...this.msg.timings,
prompt_per_second: this.msg.timings.prompt_n / (this.msg.timings.prompt_ms / 1000),
predicted_per_second: this.msg.timings.predicted_n / (this.msg.timings.predicted_ms / 1000),
};
}
},
methods: {
copyMsg() {
copyStr(this.msg.content);
},
editMsg() {
this.editUserMsgAndRegenerate({
...this.msg,
content: this.editingContent,
});
this.editingContent = null;
},
},
});
// coversations is stored in localStorage
// format: { [convId]: { id: string, lastModified: number, messages: [...] } }
// convId is a string prefixed with 'conv-'
@@ -238,29 +192,10 @@ const chatScrollToBottom = (requiresNearBottom) => {
}
};
// wrapper for SSE
async function* sendSSEPostRequest(url, fetchOptions) {
const res = await fetch(url, fetchOptions);
const lines = res.body
.pipeThrough(new TextDecoderStream())
.pipeThrough(new TextLineStream());
for await (const line of lines) {
if (isDev) console.log({line});
if (line.startsWith('data:') && !line.endsWith('[DONE]')) {
const data = JSON.parse(line.slice(5));
yield data;
} else if (line.startsWith('error:')) {
const data = JSON.parse(line.slice(6));
throw new Error(data.message || 'Unknown error');
}
}
};
const mainApp = createApp({
components: {
VueMarkdown,
SettingsModalShortInput,
MessageBubble,
},
data() {
return {
@@ -274,6 +209,7 @@ const mainApp = createApp({
selectedTheme: StorageUtils.getTheme(),
config: StorageUtils.getConfig(),
showConfigDialog: false,
editingMsg: null,
// const
themes: THEMES,
configDefault: {...CONFIG_DEFAULT},
@@ -290,15 +226,6 @@ const mainApp = createApp({
});
resizeObserver.observe(pendingMsgElem);
},
watch: {
viewingConvId: function(val, oldVal) {
if (val != oldVal) {
this.fetchMessages();
chatScrollToBottom();
this.hideSidebar();
}
}
},
methods: {
hideSidebar() {
document.getElementById('toggle-drawer').checked = false;
@@ -310,10 +237,18 @@ const mainApp = createApp({
newConversation() {
if (this.isGenerating) return;
this.viewingConvId = StorageUtils.getNewConvId();
this.editingMsg = null;
this.fetchMessages();
chatScrollToBottom();
this.hideSidebar();
},
setViewingConv(convId) {
if (this.isGenerating) return;
this.viewingConvId = convId;
this.editingMsg = null;
this.fetchMessages();
chatScrollToBottom();
this.hideSidebar();
},
deleteConv(convId) {
if (this.isGenerating) return;
@@ -321,6 +256,7 @@ const mainApp = createApp({
StorageUtils.remove(convId);
if (this.viewingConvId === convId) {
this.viewingConvId = StorageUtils.getNewConvId();
this.editingMsg = null;
}
this.fetchConversation();
this.fetchMessages();
@@ -355,6 +291,7 @@ const mainApp = createApp({
this.fetchConversation();
this.fetchMessages();
this.inputMsg = '';
this.editingMsg = null;
this.generateMessage(currConvId);
chatScrollToBottom();
},
@@ -362,6 +299,7 @@ const mainApp = createApp({
if (this.isGenerating) return;
this.pendingMsg = { id: Date.now()+1, role: 'assistant', content: null };
this.isGenerating = true;
this.editingMsg = null;
try {
const abortController = new AbortController();
@@ -392,21 +330,17 @@ const mainApp = createApp({
dry_allowed_length: this.config.dry_allowed_length,
dry_penalty_last_n: this.config.dry_penalty_last_n,
max_tokens: this.config.max_tokens,
timings_per_token: !!this.config.showTokensPerSecond,
...(this.config.custom.length ? JSON.parse(this.config.custom) : {}),
...(this.config.apiKey ? { api_key: this.config.apiKey } : {}),
};
const chunks = sendSSEPostRequest(`${BASE_URL}/v1/chat/completions`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': this.config.apiKey ? `Bearer ${this.config.apiKey}` : undefined,
},
body: JSON.stringify(params),
signal: abortController.signal,
});
for await (const chunk of chunks) {
const stop = chunk.stop;
const addedContent = chunk.choices[0].delta.content;
const config = {
controller: abortController,
api_url: BASE_URL,
endpoint: '/chat/completions',
};
for await (const chunk of llama(prompt, params, config)) {
const stop = chunk.data.stop;
const addedContent = chunk.data.choices[0].delta.content;
const lastContent = this.pendingMsg.content || '';
if (addedContent) {
this.pendingMsg = {
@@ -415,16 +349,6 @@ const mainApp = createApp({
content: lastContent + addedContent,
};
}
const timings = chunk.timings;
if (timings && this.config.showTokensPerSecond) {
// only extract what's really needed, to save some space
this.pendingMsg.timings = {
prompt_n: timings.prompt_n,
prompt_ms: timings.prompt_ms,
predicted_n: timings.predicted_n,
predicted_ms: timings.predicted_ms,
};
}
}
StorageUtils.appendMsg(currConvId, this.pendingMsg);
@@ -463,10 +387,14 @@ const mainApp = createApp({
this.fetchMessages();
this.generateMessage(currConvId);
},
copyMsg(msg) {
copyStr(msg.content);
},
editUserMsgAndRegenerate(msg) {
if (this.isGenerating) return;
const currConvId = this.viewingConvId;
const newContent = msg.content;
this.editingMsg = null;
StorageUtils.filterAndKeepMsgs(currConvId, (m) => m.id < msg.id);
StorageUtils.appendMsg(currConvId, {
id: Date.now(),

View File

@@ -394,7 +394,7 @@ int main(int raw_argc, char ** raw_argv) {
}
if (show_token_count) {
printf("Total number of tokens: %zu\n", tokens.size());
printf("Total number of tokens: %ld\n", tokens.size());
}
// silence valgrind
llama_free(ctx);

View File

@@ -32,13 +32,6 @@ else()
endif()
endif()
# remove the lib prefix on win32 mingw
if (WIN32)
set(CMAKE_STATIC_LIBRARY_PREFIX "")
set(CMAKE_SHARED_LIBRARY_PREFIX "")
set(CMAKE_SHARED_MODULE_PREFIX "")
endif()
option(BUILD_SHARED_LIBS "ggml: build shared libraries" ${BUILD_SHARED_LIBS_DEFAULT})
option(GGML_BACKEND_DL "ggml: build backends as dynamic libraries (requires BUILD_SHARED_LIBS)" OFF)

View File

@@ -228,7 +228,6 @@ extern "C" {
GGML_API void ggml_backend_unload(ggml_backend_reg_t reg);
// Load all known backends from dynamic libraries
GGML_API void ggml_backend_load_all(void);
GGML_API void ggml_backend_load_all_from_path(const char * dir_path);
//
// Backend scheduler

View File

@@ -194,6 +194,11 @@ endif()
if (WIN32)
add_compile_definitions(_CRT_SECURE_NO_WARNINGS)
if (BUILD_SHARED_LIBS)
# TODO: should not use this
set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON)
endif()
endif()
# ggml

View File

@@ -449,21 +449,11 @@ static std::string backend_filename_suffix() {
#endif
}
static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent, const char * user_search_path) {
static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent) {
// enumerate all the files that match [lib]ggml-name-*.[so|dll] in the search paths
// TODO: search system paths
std::vector<std::string> search_paths = { "./", get_executable_path() };
std::string file_prefix = backend_filename_prefix() + name + "-";
std::vector<std::string> search_paths;
if (user_search_path == nullptr) {
search_paths.push_back("./");
search_paths.push_back(get_executable_path());
} else {
#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::string best_path;
@@ -519,25 +509,21 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
}
void ggml_backend_load_all() {
ggml_backend_load_all_from_path(nullptr);
}
void ggml_backend_load_all_from_path(const char * dir_path) {
#ifdef NDEBUG
bool silent = true;
#else
bool silent = false;
#endif
ggml_backend_load_best("blas", silent, dir_path);
ggml_backend_load_best("cann", silent, dir_path);
ggml_backend_load_best("cuda", silent, dir_path);
ggml_backend_load_best("hip", silent, dir_path);
ggml_backend_load_best("kompute", silent, dir_path);
ggml_backend_load_best("metal", silent, dir_path);
ggml_backend_load_best("rpc", silent, dir_path);
ggml_backend_load_best("sycl", silent, dir_path);
ggml_backend_load_best("vulkan", silent, dir_path);
ggml_backend_load_best("musa", silent, dir_path);
ggml_backend_load_best("cpu", silent, dir_path);
ggml_backend_load_best("blas", silent);
ggml_backend_load_best("cann", silent);
ggml_backend_load_best("cuda", silent);
ggml_backend_load_best("hip", silent);
ggml_backend_load_best("kompute", silent);
ggml_backend_load_best("metal", silent);
ggml_backend_load_best("rpc", silent);
ggml_backend_load_best("sycl", silent);
ggml_backend_load_best("vulkan", silent);
ggml_backend_load_best("musa", silent);
ggml_backend_load_best("cpu", silent);
}

View File

@@ -122,7 +122,7 @@ static const char * ggml_backend_amx_buffer_type_get_name(ggml_backend_buffer_ty
}
static ggml_backend_buffer_t ggml_backend_amx_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
void * data = ggml_aligned_malloc(size);
void * data = aligned_alloc(TENSOR_ALIGNMENT, size);
if (data == NULL) {
fprintf(stderr, "%s: failed to allocate buffer of size %zu\n", __func__, size);
return NULL;

View File

@@ -126,7 +126,8 @@ struct ggml_arm_arch_features_type {
#endif
#include <windows.h>
#if defined(_MSC_VER) && !defined(__clang__)
#if !defined(__clang__)
#define GGML_CACHE_ALIGN __declspec(align(GGML_CACHE_LINE))
typedef volatile LONG atomic_int;
@@ -12944,7 +12945,7 @@ static thread_ret_t ggml_graph_compute_secondary_thread(void* data);
#include "windows.h"
// TODO: support > 64 CPUs
static bool ggml_thread_apply_affinity(bool * mask) {
bool ggml_thread_apply_affinity(bool * mask) {
HANDLE h = GetCurrentThread();
uint64_t bitmask = 0ULL;

View File

@@ -94,9 +94,7 @@ static void concat_f32_cuda(const float * x, const float * y, float * dst, int n
}
// non-contiguous kernel (slow)
template <int dim>
static __global__ void __launch_bounds__(CUDA_CONCAT_BLOCK_SIZE)
concat_f32_non_cont(
static __global__ void concat_f32_non_cont(
const char * src0,
const char * src1,
char * dst,
@@ -123,28 +121,22 @@ static __global__ void __launch_bounds__(CUDA_CONCAT_BLOCK_SIZE)
uint64_t nb0,
uint64_t nb1,
uint64_t nb2,
uint64_t nb3){
static_assert(dim >= 0 && dim <= 3);
uint64_t nb3,
int32_t dim) {
const int64_t i3 = blockIdx.z;
const int64_t i2 = blockIdx.y;
const int64_t i1 = blockIdx.x;
int64_t o[4] = {0, 0, 0, 0};
o[dim] = dim == 0 ? ne00 : (dim == 1 ? ne01 : (dim == 2 ? ne02 : ne03));
const float * x;
for (int64_t i0 = threadIdx.x; i0 < ne0; i0 += blockDim.x) {
for (int i0 = threadIdx.x; i0 < ne0; i0 += blockDim.x) {
if (i0 < ne00 && i1 < ne01 && i2 < ne02 && i3 < ne03) {
x = (const float *)(src0 + (i3 )*nb03 + (i2 )*nb02 + (i1 )*nb01 + (i0 )*nb00);
} else {
if constexpr (dim == 0) {
x = (const float *) (src1 + i3 * nb13 + i2 * nb12 + i1 * nb11 + (i0 - ne00) * nb10);
} else if constexpr (dim == 1) {
x = (const float *) (src1 + i3 * nb13 + i2 * nb12 + (i1 - ne01) * nb11 + i0 * nb10);
} else if constexpr (dim == 2) {
x = (const float *) (src1 + i3 * nb13 + (i2 - ne02) * nb12 + i1 * nb11 + i0 * nb10);
} else if constexpr (dim == 3) {
x = (const float *) (src1 + (i3 - ne03) * nb13 + i2 * nb12 + i1 * nb11 + i0 * nb10);
}
x = (const float *)(src1 + (i3 - o[3])*nb13 + (i2 - o[2])*nb12 + (i1 - o[1])*nb11 + (i0 - o[0])*nb10);
}
float * y = (float *)(dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
@@ -190,32 +182,15 @@ void ggml_cuda_op_concat(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
}
} else {
dim3 grid_dim(dst->ne[1], dst->ne[2], dst->ne[3]);
auto launch_kernel = [&](auto dim) {
concat_f32_non_cont<dim><<<grid_dim, CUDA_CONCAT_BLOCK_SIZE, 0, stream>>>(
(const char *) src0->data, (const char *) src1->data, (char *) dst->data,
concat_f32_non_cont<<<grid_dim, CUDA_CONCAT_BLOCK_SIZE, 0, stream>>>(
(const char *)src0->data,
(const char *)src1->data,
( char *)dst->data,
src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3],
src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3],
src1->ne[0], src1->ne[1], src1->ne[2], src1->ne[3],
src1->nb[0], src1->nb[1], src1->nb[2], src1->nb[3],
dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3],
dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3]);
};
switch (dim) {
case 0:
launch_kernel(std::integral_constant<int, 0>{});
break;
case 1:
launch_kernel(std::integral_constant<int, 1>{});
break;
case 2:
launch_kernel(std::integral_constant<int, 2>{});
break;
case 3:
launch_kernel(std::integral_constant<int, 3>{});
break;
default:
GGML_ABORT("Invalid dim: %d", dim);
break;
}
dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3],
dst->nb[0], dst->nb[1], dst->nb[2], dst->nb[3], dim);
}
}

View File

@@ -74,8 +74,8 @@ static inline int ggml_up(int n, int m) {
//
GGML_ATTRIBUTE_FORMAT(2, 3)
GGML_API void ggml_log_internal (enum ggml_log_level level, const char * format, ...);
GGML_API void ggml_log_callback_default(enum ggml_log_level level, const char * text, void * user_data);
void ggml_log_internal (enum ggml_log_level level, const char * format, ...);
void ggml_log_callback_default(enum ggml_log_level level, const char * text, void * user_data);
#define GGML_LOG(...) ggml_log_internal(GGML_LOG_LEVEL_NONE , __VA_ARGS__)
#define GGML_LOG_INFO(...) ggml_log_internal(GGML_LOG_LEVEL_INFO , __VA_ARGS__)
@@ -304,8 +304,8 @@ struct ggml_cgraph ggml_graph_view(struct ggml_cgraph * cgraph, int i0, int i1);
// Memory allocation
GGML_API void * ggml_aligned_malloc(size_t size);
GGML_API void ggml_aligned_free(void * ptr, size_t size);
void * ggml_aligned_malloc(size_t size);
void ggml_aligned_free(void * ptr, size_t size);
// FP16 to FP32 conversion

View File

@@ -1,13 +1,11 @@
#pragma once
#include "ggml.h"
#ifdef __cplusplus
extern "C" {
#endif
GGML_API void ggml_critical_section_start(void);
GGML_API void ggml_critical_section_end(void);
void ggml_critical_section_start(void);
void ggml_critical_section_end(void);
#ifdef __cplusplus
}

View File

@@ -162,7 +162,6 @@ struct vk_device_struct {
uint32_t subgroup_size;
uint32_t shader_core_count;
bool uma;
bool float_controls_rte_fp16;
bool subgroup_size_control;
uint32_t subgroup_min_size;
@@ -1638,59 +1637,40 @@ static void ggml_vk_load_shaders(vk_device& device) {
// Create 6 variants, {s,m,l}x{unaligned,aligned}
#define CREATE_MM(PIPELINE_NAME, NAMELC, F16ACC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
if (device->mul_mat ## ID ## _l) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->l, #NAMELC #F16ACC "_l", NAMELC ## F16ACC ## _coopmat_len, NAMELC ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1, false, true); \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->l, #NAMELC #F16ACC "_l", NAMELC ## F16ACC ## _coopmat_len, NAMELC ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1, false, true, device->subgroup_size); \
if (device->mul_mat ## ID ## _m) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->m, #NAMELC #F16ACC "_m", NAMELC ## F16ACC ## _coopmat_len, NAMELC ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1, false, true); \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->m, #NAMELC #F16ACC "_m", NAMELC ## F16ACC ## _coopmat_len, NAMELC ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1, false, true, device->subgroup_size); \
if (device->mul_mat ## ID ## _s) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->s, #NAMELC #F16ACC "_s", NAMELC ## F16ACC ## _coopmat_len, NAMELC ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1, false, true); \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->s, #NAMELC #F16ACC "_s", NAMELC ## F16ACC ## _coopmat_len, NAMELC ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1, false, true, device->subgroup_size); \
if (device->mul_mat ## ID ## _l) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_l, #NAMELC #F16ACC "_aligned_l", NAMELC ## _aligned ## F16ACC ## _coopmat_len, NAMELC ## _aligned ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, l_align, false, true); \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_l, #NAMELC #F16ACC "_aligned_l", NAMELC ## _aligned ## F16ACC ## _coopmat_len, NAMELC ## _aligned ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, l_align, false, true, device->subgroup_size); \
if (device->mul_mat ## ID ## _m) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_m, #NAMELC #F16ACC "_aligned_m", NAMELC ## _aligned ## F16ACC ## _coopmat_len, NAMELC ## _aligned ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, m_align, false, true); \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_m, #NAMELC #F16ACC "_aligned_m", NAMELC ## _aligned ## F16ACC ## _coopmat_len, NAMELC ## _aligned ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, m_align, false, true, device->subgroup_size); \
if (device->mul_mat ## ID ## _s) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_s, #NAMELC #F16ACC "_aligned_s", NAMELC ## _aligned ## F16ACC ## _coopmat_len, NAMELC ## _aligned ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, s_align, false, true); \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_s, #NAMELC #F16ACC "_aligned_s", NAMELC ## _aligned ## F16ACC ## _coopmat_len, NAMELC ## _aligned ## F16ACC ## _coopmat_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, s_align, false, true, device->subgroup_size); \
// Create 2 variants, {f16,f32} accumulator
#define CREATE_MM2(PIPELINE_NAME, NAMELC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
if (device->coopmat_acc_f16_support) { \
CREATE_MM(PIPELINE_NAME . f16acc, NAMELC, _f16acc, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
} \
if (device->coopmat_acc_f32_support) { \
CREATE_MM(PIPELINE_NAME . f32acc, NAMELC, , WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
} \
CREATE_MM(PIPELINE_NAME . f16acc, NAMELC, _f16acc, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
CREATE_MM(PIPELINE_NAME . f32acc, NAMELC, , WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
CREATE_MM(pipeline_matmul_f32, matmul_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_matmul_f32_f16, matmul_f32_f16, , wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
CREATE_MM2(pipeline_matmul_f16, matmul_f16, wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
CREATE_MM2(pipeline_matmul_f16_f32, matmul_f16_f32, wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
if (device->coopmat_acc_f16_support) {
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0].f16acc, matmul_q4_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1].f16acc, matmul_q4_1_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0].f16acc, matmul_q5_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1].f16acc, matmul_q5_1_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0].f16acc, matmul_q8_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0].f16acc, matmul_q4_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1].f16acc, matmul_q4_1_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0].f16acc, matmul_q5_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1].f16acc, matmul_q5_1_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0].f16acc, matmul_q8_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K].f16acc, matmul_q2_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K].f16acc, matmul_q3_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K].f16acc, matmul_q4_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K].f16acc, matmul_q5_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K].f16acc, matmul_q6_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
} else {
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_0].f16acc, matmul_q4_0_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_1].f16acc, matmul_q4_1_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_0].f16acc, matmul_q5_0_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_1].f16acc, matmul_q5_1_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q8_0].f16acc, matmul_q8_0_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K].f16acc, matmul_q2_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K].f16acc, matmul_q3_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K].f16acc, matmul_q4_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K].f16acc, matmul_q5_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K].f16acc, matmul_q6_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, , wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
}
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q2_K].f16acc, matmul_q2_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q3_K].f16acc, matmul_q3_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q4_K].f16acc, matmul_q4_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q5_K].f16acc, matmul_q5_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_Q6_K].f16acc, matmul_q6_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_dequant_mul_mat_mat[GGML_TYPE_IQ4_NL].f16acc, matmul_iq4_nl_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_push_constants, 3, );
// If there's not enough shared memory for row_ids and the result tile, don't create these pipelines.
if (device->mul_mat_id_s || device->mul_mat_id_m || device->mul_mat_id_l) {
@@ -1698,35 +1678,19 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM2(pipeline_matmul_id_f16, matmul_id_f16, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
CREATE_MM2(pipeline_matmul_id_f16_f32, matmul_id_f16_f32, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id);
if (device->coopmat_acc_f16_support) {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0].f16acc, matmul_id_q4_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1].f16acc, matmul_id_q4_1_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0].f16acc, matmul_id_q5_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1].f16acc, matmul_id_q5_1_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0].f16acc, matmul_id_q8_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0].f16acc, matmul_id_q4_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1].f16acc, matmul_id_q4_1_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0].f16acc, matmul_id_q5_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1].f16acc, matmul_id_q5_1_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0].f16acc, matmul_id_q8_0_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K].f16acc, matmul_id_q2_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K].f16acc, matmul_id_q3_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f16acc, matmul_id_q4_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f16acc, matmul_id_q5_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f16acc, matmul_id_q6_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
} else {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_0].f16acc, matmul_id_q4_0_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_1].f16acc, matmul_id_q4_1_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_0].f16acc, matmul_id_q5_0_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_1].f16acc, matmul_id_q5_1_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q8_0].f16acc, matmul_id_q8_0_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K].f16acc, matmul_id_q2_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K].f16acc, matmul_id_q3_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f16acc, matmul_id_q4_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f16acc, matmul_id_q5_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f16acc, matmul_id_q6_k_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, , wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
}
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q2_K].f16acc, matmul_id_q2_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q3_K].f16acc, matmul_id_q3_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q4_K].f16acc, matmul_id_q4_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q5_K].f16acc, matmul_id_q5_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f16acc, matmul_id_q6_k_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, _f16acc, wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
}
#undef CREATE_MM2
#undef CREATE_MM
} else if (device->fp16) {
// Create 6 variants, {s,m,l}x{unaligned,aligned}
@@ -1744,11 +1708,6 @@ static void ggml_vk_load_shaders(vk_device& device) {
if (device->mul_mat ## ID ## _s) \
ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_s, #NAMELC #F16ACC "_aligned_s", NAMELC ## _aligned ## F16ACC ## _len, NAMELC ## _aligned ## F16ACC ## _data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, s_align); \
// Create 2 variants, {f16,f32} accumulator
#define CREATE_MM2(PIPELINE_NAME, NAMELC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
CREATE_MM(PIPELINE_NAME . f16acc, NAMELC, _f16acc, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
CREATE_MM(PIPELINE_NAME . f32acc, NAMELC, , WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
CREATE_MM(pipeline_matmul_f32, matmul_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
CREATE_MM(pipeline_matmul_f32_f16, matmul_f32_f16, , wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
CREATE_MM2(pipeline_matmul_f16, matmul_f16, wg_denoms, warptile, vk_mat_mat_push_constants, 3, );
@@ -1786,7 +1745,6 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f16acc, matmul_id_q6_k_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f16acc, matmul_id_iq4_nl_f32, _f16acc, mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
}
#undef CREATE_MM2
#undef CREATE_MM
} else {
// Create 6 variants, {s,m,l}x{unaligned,aligned}
@@ -1841,6 +1799,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_Q6_K].f32acc, matmul_id_q6_k_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
CREATE_MM(pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL].f32acc, matmul_id_iq4_nl_f32, , mmq_wg_denoms, warptile_mmq, vk_mat_mat_id_push_constants, 4, _id);
}
#undef CREATE_MM2
#undef CREATE_MM
}
@@ -1983,26 +1942,17 @@ static void ggml_vk_load_shaders(vk_device& device) {
ggml_vk_create_pipeline(device, device->pipeline_soft_max_f32_f16_wg512, "soft_max_f32_f16_wg512", soft_max_f32_f16_len, soft_max_f32_f16_data, "main", 3, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, { 512 }, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32, "rope_norm_f32", rope_norm_f32_len, rope_norm_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_len, rope_norm_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
if (device->float_controls_rte_fp16) {
ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_rte_len, rope_norm_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_rte_len, rope_neox_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
} else {
ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_len, rope_norm_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
}
ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_argsort_f32, "argsort_f32", argsort_f32_len, argsort_f32_data, "main", 2, sizeof(vk_op_argsort_push_constants), {1024, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_sum_rows_f32, "sum_rows_f32", sum_rows_f32_len, sum_rows_f32_data, "main", 2, sizeof(vk_op_push_constants), {1, 1, 1}, { device->subgroup_size }, 1);
ggml_vk_create_pipeline(device, device->pipeline_im2col_f32, "im2col_f32", im2col_f32_len, im2col_f32_data, "main", 2, sizeof(vk_op_im2col_push_constants), {256, 1, 1}, {}, 1);
if (device->float_controls_rte_fp16) {
ggml_vk_create_pipeline(device, device->pipeline_im2col_f32_f16, "im2col_f32_f16", im2col_f32_f16_rte_len, im2col_f32_f16_rte_data, "main", 2, sizeof(vk_op_im2col_push_constants), {256, 1, 1}, {}, 1);
} else {
ggml_vk_create_pipeline(device, device->pipeline_im2col_f32_f16, "im2col_f32_f16", im2col_f32_f16_len, im2col_f32_f16_data, "main", 2, sizeof(vk_op_im2col_push_constants), {256, 1, 1}, {}, 1);
}
ggml_vk_create_pipeline(device, device->pipeline_im2col_f32_f16, "im2col_f32_f16", im2col_f32_f16_len, im2col_f32_f16_data, "main", 2, sizeof(vk_op_im2col_push_constants), {256, 1, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_timestep_embedding_f32, "timestep_embedding_f32", timestep_embedding_f32_len, timestep_embedding_f32_data, "main", 2, sizeof(vk_op_timestep_embedding_push_constants), {256, 1, 1}, {}, 1);
@@ -2085,15 +2035,13 @@ static vk_device ggml_vk_get_device(size_t idx) {
vk::PhysicalDeviceDriverProperties driver_props;
vk::PhysicalDeviceShaderSMBuiltinsPropertiesNV sm_props;
vk::PhysicalDeviceShaderCoreProperties2AMD amd_shader_core_properties2_props;
vk::PhysicalDeviceVulkan12Properties vk12_props;
vk::PhysicalDeviceSubgroupSizeControlPropertiesEXT subgroup_size_control_props;
props2.pNext = &props3;
props3.pNext = &subgroup_props;
subgroup_props.pNext = &driver_props;
driver_props.pNext = &vk12_props;
VkBaseOutStructure * last_struct = (VkBaseOutStructure *)&vk12_props;
VkBaseOutStructure * last_struct = (VkBaseOutStructure *)&driver_props;
if (maintenance4_support) {
last_struct->pNext = (VkBaseOutStructure *)&props4;
@@ -2143,17 +2091,16 @@ static vk_device ggml_vk_get_device(size_t idx) {
} else {
device->shader_core_count = 0;
}
device->float_controls_rte_fp16 = vk12_props.shaderRoundingModeRTEFloat16;
const bool force_disable_f16 = getenv("GGML_VK_DISABLE_F16") != nullptr;
device->fp16 = !force_disable_f16 && fp16_storage && fp16_compute;
if (device->vendor_id == VK_VENDOR_ID_INTEL || (device->vendor_id == VK_VENDOR_ID_AMD && (driver_props.driverID == vk::DriverId::eAmdProprietary || driver_props.driverID == vk::DriverId::eAmdOpenSource))) {
// Intel drivers don't support coopmat properly yet
// Only RADV supports coopmat properly on AMD
device->coopmat_support = false;
}
// if (device->vendor_id == VK_VENDOR_ID_INTEL || (device->vendor_id == VK_VENDOR_ID_AMD && driver_props.driverID == vk::DriverId::eAmdProprietary)) {
// // Intel drivers don't support coopmat properly yet
// // Only RADV supports coopmat properly on AMD
// device->coopmat_support = false;
// }
std::vector<vk::QueueFamilyProperties> queue_family_props = device->physical_device.getQueueFamilyProperties();
@@ -2244,8 +2191,8 @@ static vk_device ggml_vk_get_device(size_t idx) {
device->pipeline_robustness = pl_robustness_features.pipelineRobustness;
device->subgroup_size_control = device->subgroup_size_control &&
(subgroup_size_control_props.requiredSubgroupSizeStages & vk::ShaderStageFlagBits::eCompute) &&
subgroup_size_control_features.subgroupSizeControl;
(!(subgroup_size_control_props.requiredSubgroupSizeStages & vk::ShaderStageFlagBits::eCompute) ||
!subgroup_size_control_features.subgroupSizeControl);
if (device->subgroup_size_control) {
device->subgroup_min_size = subgroup_size_control_props.minSubgroupSize;
@@ -2403,7 +2350,7 @@ static vk_device ggml_vk_get_device(size_t idx) {
}
}
if (device->coopmat_m == 0 || !device->coopmat_acc_f32_support) {
if (device->coopmat_m == 0) {
// No suitable matmul mode found
GGML_LOG_DEBUG("ggml_vulkan: WARNING: No suitable matrix core mode found. Disabling matrix cores.\n");
device->coopmat_support = false;
@@ -2536,11 +2483,11 @@ static void ggml_vk_print_gpu_info(size_t idx) {
}
}
if (props2.properties.vendorID == VK_VENDOR_ID_INTEL || (props2.properties.vendorID == VK_VENDOR_ID_AMD && (driver_props.driverID == vk::DriverId::eAmdProprietary || driver_props.driverID == vk::DriverId::eAmdOpenSource))) {
// Intel drivers don't support coopmat properly yet
// Only RADV supports coopmat properly on AMD
coopmat_support = false;
}
// if (props2.properties.vendorID == VK_VENDOR_ID_INTEL || (props2.properties.vendorID == VK_VENDOR_ID_AMD && driver_props.driverID == vk::DriverId::eAmdProprietary)) {
// // Intel drivers don't support coopmat properly yet
// // Only RADV supports coopmat properly on AMD
// coopmat_support = false;
// }
const char* GGML_VK_DISABLE_F16 = getenv("GGML_VK_DISABLE_F16");
bool force_disable_f16 = GGML_VK_DISABLE_F16 != nullptr;
@@ -2823,7 +2770,7 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_pipeline(ggml_backend_vk_conte
if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F16) {
return ctx->device->pipeline_matmul_f32_f16;
}
if (prec == GGML_PREC_DEFAULT && ctx->device->fp16 && !(ctx->device->coopmat_support && !ctx->device->coopmat_acc_f16_support)) {
if (prec == GGML_PREC_DEFAULT && ctx->device->fp16) {
if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F32) {
return ctx->device->pipeline_matmul_f16_f32.f16acc;
}
@@ -2898,7 +2845,7 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_id_pipeline(ggml_backend_vk_co
if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_F32) {
return ctx->device->pipeline_matmul_id_f32;
}
if (prec == GGML_PREC_DEFAULT && ctx->device->fp16 && !(ctx->device->coopmat_support && !ctx->device->coopmat_acc_f16_support)) {
if (prec == GGML_PREC_DEFAULT && ctx->device->fp16) {
if (src0_type == GGML_TYPE_F16 && src1_type == GGML_TYPE_F32) {
return ctx->device->pipeline_matmul_id_f16_f32.f16acc;
}

View File

@@ -9,8 +9,8 @@ layout (binding = 1) writeonly buffer D {D_TYPE data_b[];};
void main() {
[[unroll]] for (uint wgy = 0; wgy < 256; wgy++) {
const uint ib = gl_WorkGroupID.x * 256 + wgy;
if (ib >= p.M * p.K / QUANT_K) {
const uint i = gl_WorkGroupID.x * 256 + wgy;
if (i >= p.M * p.K / QUANT_K) {
return;
}
@@ -20,49 +20,37 @@ void main() {
const uint is = 2 * il;
const uint n = 4;
const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].d.x);
const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].d.y);
const FLOAT_TYPE dall = FLOAT_TYPE(data_a[i].d.x);
const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[i].d.y);
const uint y_idx = ib * QUANT_K + 64 * il + n * ir;
const uint y_idx = i * QUANT_K + 64 * il + n * ir;
const uint qs_idx = 32*il + n * ir;
uint scidx0 = (is < 4) ? is : (is + 4);
uint scidx1 = (is < 4) ? is : (is - 4);
uint scidxmask1 = (is < 4) ? 0x30 : 0xC0;
uint scidxshift1 = (is < 4) ? 0 : 2;
uint mbidx0 = is + 4;
uint mbidx1 = (is < 4) ? is + 4 : is;
uint mbidxmask0 = (is < 4) ? 0xF : 0xF0;
uint mbidxshift0 = (is < 4) ? 0 : 4;
uint mbidxmask1 = (is < 4) ? 0x30 : 0xC0;
uint mbidxshift1 = (is < 4) ? 0 : 2;
uint8_t sc = uint8_t((data_a[ib].scales[scidx0] & 0xF) | ((data_a[ib].scales[scidx1] & scidxmask1) >> scidxshift1));
uint8_t mbyte = uint8_t((data_a[ib].scales[mbidx0] & mbidxmask0) >> mbidxshift0 | ((data_a[ib].scales[mbidx1] & mbidxmask1) >> mbidxshift1));
uint8_t sc;
uint8_t m;
if (is < 4) {
sc = uint8_t(data_a[i].scales[is] & 63);
m = uint8_t(data_a[i].scales[is + 4] & 63);
} else {
sc = uint8_t((data_a[i].scales[is + 4] & 0xF) | ((data_a[i].scales[is - 4] >> 6) << 4));
m = uint8_t((data_a[i].scales[is + 4] >> 4) | ((data_a[i].scales[is ] >> 6) << 4));
}
const FLOAT_TYPE d1 = dall * sc;
const FLOAT_TYPE m1 = dmin * mbyte;
scidx0 = (is < 4) ? is + 1 : (is + 5);
scidx1 = (is < 4) ? is + 1 : (is - 3);
scidxmask1 = (is < 4) ? 0x30 : 0xC0;
scidxshift1 = (is < 4) ? 0 : 2;
mbidx0 = is + 5;
mbidx1 = (is < 4) ? is + 5 : is + 1;
mbidxmask0 = (is < 4) ? 0xF : 0xF0;
mbidxshift0 = (is < 4) ? 0 : 4;
mbidxmask1 = (is < 4) ? 0x30 : 0xC0;
mbidxshift1 = (is < 4) ? 0 : 2;
sc = uint8_t((data_a[ib].scales[scidx0] & 0xF) | ((data_a[ib].scales[scidx1] & scidxmask1) >> scidxshift1));
mbyte = uint8_t((data_a[ib].scales[mbidx0] & mbidxmask0) >> mbidxshift0 | ((data_a[ib].scales[mbidx1] & mbidxmask1) >> mbidxshift1));
const FLOAT_TYPE m1 = dmin * m;
if (is < 4) {
sc = uint8_t(data_a[i].scales[is + 1] & 63);
m = uint8_t(data_a[i].scales[is + 5] & 63);
} else {
sc = uint8_t((data_a[i].scales[is + 5] & 0xF) | ((data_a[i].scales[is - 3] >> 6) << 4));
m = uint8_t((data_a[i].scales[is + 5] >> 4) | ((data_a[i].scales[is + 1] >> 6) << 4));
}
const FLOAT_TYPE d2 = dall * sc;
const FLOAT_TYPE m2 = dmin * mbyte;
const FLOAT_TYPE m2 = dmin * m;
[[unroll]] for (uint l = 0; l < n; ++l) {
data_b[y_idx + l ] = D_TYPE(d1 * FLOAT_TYPE(data_a[ib].qs[qs_idx + l] & 0xF) - m1);
data_b[y_idx + l + 32] = D_TYPE(d2 * FLOAT_TYPE(data_a[ib].qs[qs_idx + l] >> 4) - m2);
data_b[y_idx + l ] = D_TYPE(d1 * FLOAT_TYPE(data_a[i].qs[qs_idx + l] & 0xF) - m1);
data_b[y_idx + l + 32] = D_TYPE(d2 * FLOAT_TYPE(data_a[i].qs[qs_idx + l] >> 4) - m2);
}
}
}

View File

@@ -9,8 +9,8 @@ layout (binding = 1) writeonly buffer D {D_TYPE data_b[];};
void main() {
[[unroll]] for (uint wgy = 0; wgy < 256; wgy++) {
const uint ib = gl_WorkGroupID.x * 256 + wgy;
if (ib >= p.M * p.K / QUANT_K) {
const uint i = gl_WorkGroupID.x * 256 + wgy;
if (i >= p.M * p.K / QUANT_K) {
return;
}
@@ -19,52 +19,40 @@ void main() {
const uint ir = tid % 16;
const uint is = 2 * il;
const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].d.x);
const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].d.y);
const FLOAT_TYPE dall = FLOAT_TYPE(data_a[i].d.x);
const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[i].d.y);
const uint y_idx = ib * QUANT_K + 64 * il + 2 * ir;
const uint y_idx = i * QUANT_K + 64 * il + 2 * ir;
const uint qs_idx = 32*il + 2 * ir;
const uint qh_idx = 2 * ir;
uint scidx0 = (is < 4) ? is : (is + 4);
uint scidx1 = (is < 4) ? is : (is - 4);
uint scidxmask1 = (is < 4) ? 0x30 : 0xC0;
uint scidxshift1 = (is < 4) ? 0 : 2;
uint mbidx0 = is + 4;
uint mbidx1 = (is < 4) ? is + 4 : is;
uint mbidxmask0 = (is < 4) ? 0xF : 0xF0;
uint mbidxshift0 = (is < 4) ? 0 : 4;
uint mbidxmask1 = (is < 4) ? 0x30 : 0xC0;
uint mbidxshift1 = (is < 4) ? 0 : 2;
uint8_t sc = uint8_t((data_a[ib].scales[scidx0] & 0xF) | ((data_a[ib].scales[scidx1] & scidxmask1) >> scidxshift1));
uint8_t mbyte = uint8_t((data_a[ib].scales[mbidx0] & mbidxmask0) >> mbidxshift0 | ((data_a[ib].scales[mbidx1] & mbidxmask1) >> mbidxshift1));
uint8_t sc;
uint8_t m;
if (is < 4) {
sc = uint8_t(data_a[i].scales[is] & 63);
m = uint8_t(data_a[i].scales[is + 4] & 63);
} else {
sc = uint8_t((data_a[i].scales[is + 4] & 0xF) | ((data_a[i].scales[is - 4] >> 6) << 4));
m = uint8_t((data_a[i].scales[is + 4] >> 4) | ((data_a[i].scales[is ] >> 6) << 4));
}
const FLOAT_TYPE d1 = dall * sc;
const FLOAT_TYPE m1 = dmin * mbyte;
scidx0 = (is < 4) ? is + 1 : (is + 5);
scidx1 = (is < 4) ? is + 1 : (is - 3);
scidxmask1 = (is < 4) ? 0x30 : 0xC0;
scidxshift1 = (is < 4) ? 0 : 2;
mbidx0 = is + 5;
mbidx1 = (is < 4) ? is + 5 : is + 1;
mbidxmask0 = (is < 4) ? 0xF : 0xF0;
mbidxshift0 = (is < 4) ? 0 : 4;
mbidxmask1 = (is < 4) ? 0x30 : 0xC0;
mbidxshift1 = (is < 4) ? 0 : 2;
sc = uint8_t((data_a[ib].scales[scidx0] & 0xF) | ((data_a[ib].scales[scidx1] & scidxmask1) >> scidxshift1));
mbyte = uint8_t((data_a[ib].scales[mbidx0] & mbidxmask0) >> mbidxshift0 | ((data_a[ib].scales[mbidx1] & mbidxmask1) >> mbidxshift1));
const FLOAT_TYPE m1 = dmin * m;
if (is < 4) {
sc = uint8_t(data_a[i].scales[is + 1] & 63);
m = uint8_t(data_a[i].scales[is + 5] & 63);
} else {
sc = uint8_t((data_a[i].scales[is + 5] & 0xF) | ((data_a[i].scales[is - 3] >> 6) << 4));
m = uint8_t((data_a[i].scales[is + 5] >> 4) | ((data_a[i].scales[is + 1] >> 6) << 4));
}
const FLOAT_TYPE d2 = dall * sc;
const FLOAT_TYPE m2 = dmin * mbyte;
const FLOAT_TYPE m2 = dmin * m;
const uint8_t hm1 = uint8_t(1 << (2 * il ));
const uint8_t hm2 = uint8_t(1 << (2 * il + 1));
data_b[y_idx ] = D_TYPE(d1 * FLOAT_TYPE((data_a[ib].qs[qs_idx ] & 0xF) + (((data_a[ib].qh[qh_idx ] & hm1) != 0) ? 16 : 0)) - m1);
data_b[y_idx + 1] = D_TYPE(d1 * FLOAT_TYPE((data_a[ib].qs[qs_idx + 1] & 0xF) + (((data_a[ib].qh[qh_idx + 1] & hm1) != 0) ? 16 : 0)) - m1);
data_b[y_idx + 32] = D_TYPE(d2 * FLOAT_TYPE((data_a[ib].qs[qs_idx ] >> 4) + (((data_a[ib].qh[qh_idx ] & hm2) != 0) ? 16 : 0)) - m2);
data_b[y_idx + 33] = D_TYPE(d2 * FLOAT_TYPE((data_a[ib].qs[qs_idx + 1] >> 4) + (((data_a[ib].qh[qh_idx + 1] & hm2) != 0) ? 16 : 0)) - m2);
data_b[y_idx ] = D_TYPE(d1 * FLOAT_TYPE((data_a[i].qs[qs_idx ] & 0xF) + (((data_a[i].qh[qh_idx ] & hm1) != 0) ? 16 : 0)) - m1);
data_b[y_idx + 1] = D_TYPE(d1 * FLOAT_TYPE((data_a[i].qs[qs_idx + 1] & 0xF) + (((data_a[i].qh[qh_idx + 1] & hm1) != 0) ? 16 : 0)) - m1);
data_b[y_idx + 32] = D_TYPE(d2 * FLOAT_TYPE((data_a[i].qs[qs_idx ] >> 4) + (((data_a[i].qh[qh_idx ] & hm2) != 0) ? 16 : 0)) - m2);
data_b[y_idx + 33] = D_TYPE(d2 * FLOAT_TYPE((data_a[i].qs[qs_idx + 1] >> 4) + (((data_a[i].qh[qh_idx + 1] & hm2) != 0) ? 16 : 0)) - m2);
}
}

View File

@@ -1,11 +1,6 @@
#version 450
#extension GL_EXT_shader_16bit_storage : require
#extension GL_EXT_spirv_intrinsics: enable
#if RTE16
spirv_execution_mode(capabilities = [4467], 4462, 16); // RoundingModeRTE, 16 bits
#endif
layout (push_constant) uniform parameter
{

View File

@@ -1,11 +1,6 @@
#include "types.comp"
#extension GL_EXT_shader_16bit_storage : require
#extension GL_EXT_spirv_intrinsics: enable
#if RTE16
spirv_execution_mode(capabilities = [4467], 4462, 16); // RoundingModeRTE, 16 bits
#endif
layout(local_size_x = 1, local_size_y = 256, local_size_z = 1) in;

View File

@@ -461,11 +461,9 @@ void process_shaders() {
string_to_spv("rope_norm_f32", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("rope_norm_f16", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
string_to_spv("rope_norm_f16_rte", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
string_to_spv("rope_neox_f32", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
string_to_spv("rope_neox_f16", "rope_neox.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
string_to_spv("rope_neox_f16_rte", "rope_neox.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
string_to_spv("argsort_f32", "argsort.comp", {{"A_TYPE", "float"}});
@@ -473,7 +471,6 @@ void process_shaders() {
string_to_spv("im2col_f32", "im2col.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));
string_to_spv("im2col_f32_f16", "im2col.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}}));
string_to_spv("im2col_f32_f16_rte", "im2col.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}}));
string_to_spv("timestep_embedding_f32", "timestep_embedding.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"D_TYPE", "float"}}));

View File

@@ -1,6 +1,6 @@
[tool.poetry]
name = "gguf"
version = "0.11.0"
version = "0.10.0"
description = "Read and write ML models in GGUF for GGML"
authors = ["GGML <ggml@ggml.ai>"]
packages = [

View File

@@ -456,7 +456,6 @@ extern "C" {
// Functions to access the model's GGUF metadata scalar values
// - The functions return the length of the string on success, or -1 on failure
// - The output string is always null-terminated and cleared on failure
// - When retrieving a string, an extra byte must be allocated to account for the null terminator
// - GGUF array values are not supported by these functions
// Get metadata value as a string by key name

View File

@@ -1,3 +1,10 @@
# TODO: should not use this
if (WIN32)
if (BUILD_SHARED_LIBS)
set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON)
endif()
endif()
llama_add_compile_flags()
#

View File

@@ -1794,7 +1794,7 @@ private:
DWORD bufLen = FormatMessageA(FORMAT_MESSAGE_ALLOCATE_BUFFER | FORMAT_MESSAGE_FROM_SYSTEM | FORMAT_MESSAGE_IGNORE_INSERTS,
NULL, error_code, MAKELANGID(LANG_NEUTRAL, SUBLANG_DEFAULT), (LPSTR)&lpMsgBuf, 0, NULL);
if (!bufLen) {
ret = format("Win32 error code: %lx", error_code);
ret = format("Win32 error code: %s", error_code);
} else {
ret = lpMsgBuf;
LocalFree(lpMsgBuf);
@@ -2132,7 +2132,7 @@ struct llama_mmap {
HMODULE hKernel32 = GetModuleHandleW(L"kernel32.dll");
// may fail on pre-Windows 8 systems
pPrefetchVirtualMemory = (decltype(pPrefetchVirtualMemory))(void *) GetProcAddress(hKernel32, "PrefetchVirtualMemory");
pPrefetchVirtualMemory = reinterpret_cast<decltype(pPrefetchVirtualMemory)> (GetProcAddress(hKernel32, "PrefetchVirtualMemory"));
if (pPrefetchVirtualMemory) {
// advise the kernel to preload the mapped memory
@@ -21577,7 +21577,7 @@ float * llama_get_embeddings_ith(struct llama_context * ctx, int32_t i) {
throw std::runtime_error(format("negative index out of range [0, %d)", ctx->n_outputs));
}
} else if ((size_t) i >= ctx->output_ids.size()) {
throw std::runtime_error(format("out of range [0, %zu)", ctx->output_ids.size()));
throw std::runtime_error(format("out of range [0, %lu)", ctx->output_ids.size()));
} else {
j = ctx->output_ids[i];
}

View File

@@ -84,50 +84,38 @@ llama_test(test-tokenizer-0 NAME test-tokenizer-0-qwen2 ARGS ${CMAKE
llama_test(test-tokenizer-0 NAME test-tokenizer-0-refact ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-refact.gguf)
llama_test(test-tokenizer-0 NAME test-tokenizer-0-starcoder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf)
# build test-tokenizer-1-bpe target once and add many tests
add_executable(test-tokenizer-1-bpe test-tokenizer-1-bpe.cpp)
target_link_libraries(test-tokenizer-1-bpe PRIVATE common)
install(TARGETS test-tokenizer-1-bpe RUNTIME)
if (NOT WIN32)
# these tests are disabled on Windows because they use internal functions not exported with LLAMA_API
llama_target_and_test(test-sampling.cpp)
llama_target_and_test(test-grammar-parser.cpp)
llama_target_and_test(test-grammar-integration.cpp)
llama_target_and_test(test-llama-grammar.cpp)
# TODO: disabled on loongarch64 because the ggml-ci node lacks Python 3.8
if (NOT ${CMAKE_SYSTEM_PROCESSOR} MATCHES "loongarch64")
llama_target_and_test(test-json-schema-to-grammar.cpp WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/..)
target_include_directories(test-json-schema-to-grammar PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/../examples/server)
endif()
# TODO: disabled due to slowness
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-aquila ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-aquila.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-falcon ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-gpt-2 ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt-2.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-gpt-neox ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt-neox.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-llama-bpe ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf --ignore-merges)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-mpt ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-refact ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-refact.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-starcoder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf)
# build test-tokenizer-1-spm target once and add many tests
add_executable(test-tokenizer-1-spm test-tokenizer-1-spm.cpp)
target_link_libraries(test-tokenizer-1-spm PRIVATE common)
install(TARGETS test-tokenizer-1-spm RUNTIME)
# build test-tokenizer-1-bpe target once and add many tests
add_executable(test-tokenizer-1-bpe test-tokenizer-1-bpe.cpp)
target_link_libraries(test-tokenizer-1-bpe PRIVATE common)
install(TARGETS test-tokenizer-1-bpe RUNTIME)
# TODO: disabled due to slowness
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-aquila ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-aquila.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-falcon ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-falcon.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-gpt-2 ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt-2.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-gpt-neox ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-gpt-neox.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-llama-bpe ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-bpe.gguf --ignore-merges)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-mpt ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-mpt.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-refact ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-refact.gguf)
#llama_test(test-tokenizer-1-bpe NAME test-tokenizer-1-starcoder ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-starcoder.gguf)
# build test-tokenizer-1-spm target once and add many tests
add_executable(test-tokenizer-1-spm test-tokenizer-1-spm.cpp)
target_link_libraries(test-tokenizer-1-spm PRIVATE common)
install(TARGETS test-tokenizer-1-spm RUNTIME)
llama_test(test-tokenizer-1-spm NAME test-tokenizer-1-llama-spm ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-spm.gguf)
#llama_test(test-tokenizer-1-spm NAME test-tokenizer-1-baichuan ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-baichuan.gguf)
# llama_target_and_test(test-double-float.cpp) # SLOW
endif()
llama_test(test-tokenizer-1-spm NAME test-tokenizer-1-llama-spm ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-llama-spm.gguf)
#llama_test(test-tokenizer-1-spm NAME test-tokenizer-1-baichuan ARGS ${CMAKE_CURRENT_SOURCE_DIR}/../models/ggml-vocab-baichuan.gguf)
# llama_target_and_test(test-double-float.cpp) # SLOW
llama_target_and_test(test-log.cpp)
llama_target_and_test(test-arg-parser.cpp)
llama_target_and_test(test-sampling.cpp)
llama_target_and_test(test-chat-template.cpp)
llama_target_and_test(test-grammar-parser.cpp)
llama_target_and_test(test-grammar-integration.cpp)
llama_target_and_test(test-llama-grammar.cpp)
# llama_target_and_test(test-opt.cpp) # SLOW
llama_target_and_test(test-backend-ops.cpp)
@@ -142,6 +130,11 @@ if (NOT GGML_BACKEND_DL)
llama_target_and_test(test-rope.cpp)
endif()
# TODO: disabled on loongarch64 because the ggml-ci node lacks Python 3.8
if (NOT ${CMAKE_SYSTEM_PROCESSOR} MATCHES "loongarch64")
llama_target_and_test(test-json-schema-to-grammar.cpp WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/..)
target_include_directories(test-json-schema-to-grammar PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/../examples/server)
endif()
# dummy executable - not installed
get_filename_component(TEST_TARGET test-c.c NAME_WE)