vbatts/llama.cpp
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Merge branch 'master' into concedo_experimental

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# Conflicts:
#	.github/workflows/build.yml
#	Makefile
#	README.md
This commit is contained in:
Concedo 2023-05-07 19:10:01 +08:00
commit 62beded0e7
7 changed files with 20 additions and 24 deletions
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1
.gitignore vendored
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@ -21,6 +21,7 @@ build-sanitize-addr/
build-sanitize-thread/
models/*
*.bin
/main
/quantize

7
Makefile
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@ -16,12 +16,7 @@ ifndef UNAME_M
UNAME_M := $(shell uname -m)
endif
ARCH_LINUX1 := $(shell grep "Arch Linux" /etc/os-release 2>/dev/null)
ARCH_LINUX2 := $(shell grep "ID_LIKE=arch" /etc/os-release 2>/dev/null)
ifdef ARCH_LINUX1
ARCH_ADD = -lcblas
endif
ifdef ARCH_LINUX2
ifneq ($(shell grep -e "Arch Linux" -e "ID_LIKE=arch" /etc/os-release 2>/dev/null),)
ARCH_ADD = -lcblas
endif

8
examples/main/main.cpp
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@ -444,10 +444,10 @@ int main(int argc, char ** argv) {
id = llama_sample_token_mirostat_v2(ctx, &candidates_p, mirostat_tau, mirostat_eta, &mirostat_mu);
} else {
// Temperature sampling
llama_sample_top_k(ctx, &candidates_p, top_k);
llama_sample_tail_free(ctx, &candidates_p, tfs_z);
llama_sample_typical(ctx, &candidates_p, typical_p);
llama_sample_top_p(ctx, &candidates_p, top_p);
llama_sample_top_k(ctx, &candidates_p, top_k, 1);
llama_sample_tail_free(ctx, &candidates_p, tfs_z, 1);
llama_sample_typical(ctx, &candidates_p, typical_p, 1);
llama_sample_top_p(ctx, &candidates_p, top_p, 1);
llama_sample_temperature(ctx, &candidates_p, temp);
id = llama_sample_token(ctx, &candidates_p);
}

10
gpttype_adapter.cpp
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@ -114,7 +114,7 @@ llama_token sample_token_mirostat(int n_vocab, llama_token_data_array * candidat
float epsilon_hat = s_hat - 1;
float k = powf((epsilon_hat * powf(2, *mu)) / (1 - powf(N, -epsilon_hat)), 1 / s_hat);
// Sample the next word X using top-k sampling
llama_sample_top_k(nullptr, candidates, int(k));
llama_sample_top_k(nullptr, candidates, int(k),1);
llama_token X = sample_token(candidates, rng); // Compute error as the difference between observed surprise and target surprise value
size_t X_idx = std::distance(candidates->data, std::find_if(candidates->data, candidates->data + candidates->size, [&](const llama_token_data & candidate) {
return candidate.id == X;
@ -194,10 +194,10 @@ int mirostat, float mirostat_tau, float mirostat_eta)
else
{
// Temperature sampling
llama_sample_top_k(nullptr, &candidates_p, top_k);
llama_sample_tail_free(nullptr, &candidates_p, tfs);
llama_sample_typical(nullptr, &candidates_p, typical_p);
llama_sample_top_p(nullptr, &candidates_p, top_p);
llama_sample_top_k(nullptr, &candidates_p, top_k,1);
llama_sample_tail_free(nullptr, &candidates_p, tfs,1);
llama_sample_typical(nullptr, &candidates_p, typical_p,1);
llama_sample_top_p(nullptr, &candidates_p, top_p,1);
llama_sample_temperature(nullptr, &candidates_p, temp);
id = sample_token(&candidates_p, rng);
}

2
llama.cpp
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@ -1801,7 +1801,7 @@ llama_token llama_sample_token_mirostat(struct llama_context * ctx, llama_token_
float k = powf((epsilon_hat * powf(2, *mu)) / (1 - powf(N, -epsilon_hat)), 1 / s_hat);
// Sample the next word X using top-k sampling
llama_sample_top_k(nullptr, candidates, int(k));
llama_sample_top_k(nullptr, candidates, int(k), 1);
if (ctx) {
ctx->t_sample_us += ggml_time_us() - t_start_sample_us;
}

8
llama.h
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@ -202,16 +202,16 @@ extern "C" {
LLAMA_API void llama_sample_softmax(struct llama_context * ctx, llama_token_data_array * candidates);
/// @details Top-K sampling described in academic paper "The Curious Case of Neural Text Degeneration" https://arxiv.org/abs/1904.09751
LLAMA_API void llama_sample_top_k(struct llama_context * ctx, llama_token_data_array * candidates, int k, size_t min_keep = 1);
LLAMA_API void llama_sample_top_k(struct llama_context * ctx, llama_token_data_array * candidates, int k, size_t min_keep);
/// @details Nucleus sampling described in academic paper "The Curious Case of Neural Text Degeneration" https://arxiv.org/abs/1904.09751
LLAMA_API void llama_sample_top_p(struct llama_context * ctx, llama_token_data_array * candidates, float p, size_t min_keep = 1);
LLAMA_API void llama_sample_top_p(struct llama_context * ctx, llama_token_data_array * candidates, float p, size_t min_keep);
/// @details Tail Free Sampling described in https://www.trentonbricken.com/Tail-Free-Sampling/.
LLAMA_API void llama_sample_tail_free(struct llama_context * ctx, llama_token_data_array * candidates, float z, size_t min_keep = 1);
LLAMA_API void llama_sample_tail_free(struct llama_context * ctx, llama_token_data_array * candidates, float z, size_t min_keep);
/// @details Locally Typical Sampling implementation described in the paper https://arxiv.org/abs/2202.00666.
LLAMA_API void llama_sample_typical(struct llama_context * ctx, llama_token_data_array * candidates, float p, size_t min_keep = 1);
LLAMA_API void llama_sample_typical(struct llama_context * ctx, llama_token_data_array * candidates, float p, size_t min_keep);
LLAMA_API void llama_sample_temperature(struct llama_context * ctx, llama_token_data_array * candidates, float temp);
/// @details Mirostat 1.0 algorithm described in the paper https://arxiv.org/abs/2007.14966. Uses tokens instead of words.

8
tests/test-sampling.cpp
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@ -32,7 +32,7 @@ void test_top_k(const std::vector<float> & probs,
llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
llama_sample_softmax(nullptr, &candidates_p);
DUMP(&candidates_p);
llama_sample_top_k(nullptr, &candidates_p, k);
llama_sample_top_k(nullptr, &candidates_p, k, 1);
DUMP(&candidates_p);
assert(candidates_p.size == expected_probs.size());
@ -57,7 +57,7 @@ void test_top_p(const std::vector<float> & probs,
llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
llama_sample_softmax(nullptr, &candidates_p);
DUMP(&candidates_p);
llama_sample_top_p(nullptr, &candidates_p, p);
llama_sample_top_p(nullptr, &candidates_p, p, 1);
DUMP(&candidates_p);
assert(candidates_p.size == expected_probs.size());
@ -80,7 +80,7 @@ void test_tfs(const std::vector<float> & probs,
llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
DUMP(&candidates_p);
llama_sample_tail_free(nullptr, &candidates_p, z);
llama_sample_tail_free(nullptr, &candidates_p, z, 1);
DUMP(&candidates_p);
assert(candidates_p.size == expected_probs.size());
@ -103,7 +103,7 @@ void test_typical(const std::vector<float> & probs,
llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
DUMP(&candidates_p);
llama_sample_typical(nullptr, &candidates_p, p);
llama_sample_typical(nullptr, &candidates_p, p, 1);
DUMP(&candidates_p);
assert(candidates_p.size == expected_probs.size());