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Remove default arguments from sampling functions #1343

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merged 3 commits into from
May 6, 2023
Merged

Remove default arguments from sampling functions #1343

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5d46405
Add *.bin to gitignore
j-f1 May 6, 2023
46879f3
Remove default arguments from sampling functions
j-f1 May 6, 2023
fb9e1dd
Add missing parameters to examples & tests
j-f1 May 6, 2023
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1 change: 1 addition & 0 deletions .gitignore
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Expand Up @@ -21,6 +21,7 @@ build-sanitize-addr/
build-sanitize-thread/

models/*
*.bin

/main
/quantize
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8 changes: 4 additions & 4 deletions examples/main/main.cpp
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Expand Up @@ -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);
}
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2 changes: 1 addition & 1 deletion llama.cpp
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Expand Up @@ -1791,7 +1791,7 @@ 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;
}
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8 changes: 4 additions & 4 deletions llama.h
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Expand Up @@ -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.
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8 changes: 4 additions & 4 deletions tests/test-sampling.cpp
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Expand Up @@ -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());
Expand All @@ -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());
Expand All @@ -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());
Expand All @@ -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());
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