vbatts/llama.cpp
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rename n_ctx to kv_size

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Pierrick HYMBERT 2024-02-18 20:59:26 +01:00 • committed by Georgi Gerganov
parent ef96e8b1f7
commit 606873401c
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GPG key ID: 449E073F9DC10735
48 changed files with 403 additions and 393 deletions
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12
tests/test-backend-ops.cpp
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@ -1121,21 +1121,21 @@ struct test_rope : public test_case {
const std::array<int64_t, 4> ne;
int n_dims;
int mode;
int n_ctx;
int kv_size;
std::string vars() override {
return VARS_TO_STR5(type, ne, n_dims, mode, n_ctx);
return VARS_TO_STR5(type, ne, n_dims, mode, kv_size);
}
test_rope(ggml_type type = GGML_TYPE_F32,
std::array<int64_t, 4> ne = {10, 10, 10, 1},
int n_dims = 10, int mode = 0, int n_ctx = 512)
: type(type), ne(ne), n_dims(n_dims), mode(mode), n_ctx(n_ctx) {}
: type(type), ne(ne), n_dims(n_dims), mode(mode), kv_size(n_ctx) {}
ggml_tensor * build_graph(ggml_context * ctx) override {
ggml_tensor * a = ggml_new_tensor(ctx, type, 4, ne.data());
ggml_tensor * pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne[2]);
ggml_tensor * out = ggml_rope(ctx, a, pos, n_dims, mode, n_ctx);
ggml_tensor * out = ggml_rope(ctx, a, pos, n_dims, mode, kv_size);
return out;
}
@ -1145,7 +1145,7 @@ struct test_rope : public test_case {
// pos
std::vector<int> data(ne[2]);
for (int i = 0; i < ne[2]; i++) {
data[i] = rand() % n_ctx;
data[i] = rand() % kv_size;
}
ggml_backend_tensor_set(t, data.data(), 0, ne[2] * sizeof(int));
} else {
@ -1545,7 +1545,7 @@ struct llama_hparams {
int32_t n_tokens;
// llm_build_context
static constexpr int32_t n_kv = 32; // size of KV cache to consider (n_kv <= n_ctx
static constexpr int32_t n_kv = 32; // size of KV cache to consider (n_kv <= kv_size
static constexpr int32_t kv_head = 1; // index of where we store new KV data in the cache
uint32_t n_embd_gqa() const { // dimension of key embeddings across all k-v heads