vbatts/llama.cpp
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ci : integrate with ggml-org/ci (#2250)

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* ci : run ctest

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* ci : add open llama 3B-v2 tests

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* ci : disable wget progress output

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* ci : add open llama 3B-v2 tg tests for q4 and q5 quantizations

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* tests : try to fix tail free sampling test

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* ci : add K-quants

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* ci : add short perplexity tests

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* ci : add README.md

* ppl : add --chunks argument to limit max number of chunks

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* ci : update README
This commit is contained in:
Georgi Gerganov 2023-07-18 14:24:43 +03:00 • committed by GitHub
parent 6cbf9dfb32
commit d01bccde9f
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8 changed files with 312 additions and 6 deletions
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7
examples/common.cpp
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@ -279,6 +279,12 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
break;
}
params.n_keep = std::stoi(argv[i]);
} else if (arg == "--chunks") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.n_chunks = std::stoi(argv[i]);
} else if (arg == "-m" || arg == "--model") {
if (++i >= argc) {
invalid_param = true;
@ -515,6 +521,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(stderr, " -b N, --batch-size N batch size for prompt processing (default: %d)\n", params.n_batch);
fprintf(stderr, " --perplexity compute perplexity over the prompt\n");
fprintf(stderr, " --keep number of tokens to keep from the initial prompt (default: %d, -1 = all)\n", params.n_keep);
fprintf(stderr, " --chunks N max number of chunks to process (default: %d, -1 = all)\n", params.n_chunks);
if (llama_mlock_supported()) {
fprintf(stderr, " --mlock force system to keep model in RAM rather than swapping or compressing\n");
}

1
examples/common.h
View file

@ -28,6 +28,7 @@ struct gpt_params {
int32_t n_ctx = 512; // context size
int32_t n_batch = 512; // batch size for prompt processing (must be >=32 to use BLAS)
int32_t n_keep = 0; // number of tokens to keep from initial prompt
int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
int32_t n_gpu_layers = 0; // number of layers to store in VRAM
int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
float tensor_split[LLAMA_MAX_DEVICES] = {0}; // how split tensors should be distributed across GPUs

6
examples/perplexity/perplexity.cpp
View file

@ -32,13 +32,15 @@ void perplexity(llama_context * ctx, const gpt_params & params) {
// BOS tokens will be added for each chunk before eval
auto tokens = ::llama_tokenize(ctx, params.prompt, true);
int count = 0;
const int n_chunk_max = tokens.size() / params.n_ctx;
const int n_chunk = tokens.size() / params.n_ctx;
const int n_chunk = params.n_chunks < 0 ? n_chunk_max : std::min(params.n_chunks, n_chunk_max);
const int n_vocab = llama_n_vocab(ctx);
const int n_batch = params.n_batch;
int count = 0;
double nll = 0.0;
fprintf(stderr, "%s: calculating perplexity over %d chunks, batch_size=%d\n", __func__, n_chunk, n_batch);
for (int i = 0; i < n_chunk; ++i) {