vbatts/llama.cpp
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mamba : remove some useless comments

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This commit is contained in:
Francis Couture-Harpin 2024-02-04 18:25:14 -05:00
parent de92f15634
commit 766db753c8
1 changed files with 2 additions and 6 deletions
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llama.cpp
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@ -4697,9 +4697,6 @@ static bool llm_load_tensors(
auto & layer = model.layers[i]; auto & layer = model.layers[i];
// TODO: what's the difference between ctx_layer and ctx_split?
// A: It seems that ctx_split is for matrices (2d???) while ctx_layer is for other things (like 1D bias and norms, probably.)
// norm // norm
layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}); layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
@ -7910,7 +7907,6 @@ struct llm_build_context {
const int32_t n_tok = batch.n_tokens; const int32_t n_tok = batch.n_tokens;
// hopefully the compiler does constant folding
const int64_t d_model = n_embd; const int64_t d_model = n_embd;
const int64_t d_inner = n_head; const int64_t d_inner = n_head;
GGML_ASSERT(2 * d_model == d_inner); GGML_ASSERT(2 * d_model == d_inner);
@ -7957,8 +7953,8 @@ struct llm_build_context {
// The following tensor is too big in order to avoid an assertion error when making an overlapping view. // The following tensor is too big in order to avoid an assertion error when making an overlapping view.
// TODO: in ggml_new_tensor_impl, handle overlapping data range in data size calculation // TODO: in ggml_new_tensor_impl, handle overlapping data range in data size calculation
// This could then be a tensor with ne[] = {(d_conv-1)+n_tok, d_inner} // This could then be a tensor with ne[] = {(d_conv-1)+n_tok, d_inner},
// which is around (d_conv-1) times as small as its current size. // but the size difference is not that big (d_conv is usually 4).
struct ggml_tensor * conv_x = ggml_new_tensor_1d(ctx0, conv_state->type, d_conv*d_inner*n_tok); struct ggml_tensor * conv_x = ggml_new_tensor_1d(ctx0, conv_state->type, d_conv*d_inner*n_tok);
const size_t conv_x_nb1 = (d_conv - 1 + n_tok) * ggml_element_size(conv_x); const size_t conv_x_nb1 = (d_conv - 1 + n_tok) * ggml_element_size(conv_x);