diff --git a/common/common.cpp b/common/common.cpp index b2cb0e257..3aefed01d 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1055,6 +1055,9 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params & } static ggml_type kv_cache_type_from_str(const std::string & s) { + if (s == "f32") { + return GGML_TYPE_F32; + } if (s == "f16") { return GGML_TYPE_F16; } diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py index 203eaf64b..813aeeed6 100755 --- a/convert-hf-to-gguf.py +++ b/convert-hf-to-gguf.py @@ -817,10 +817,17 @@ class PersimmonModel(Model): hidden_size = self.hparams["hidden_size"] self.gguf_writer.add_name('persimmon-8b-chat') + self.gguf_writer.add_context_length(self.hparams["max_position_embeddings"]) self.gguf_writer.add_embedding_length(hidden_size) self.gguf_writer.add_block_count(block_count) self.gguf_writer.add_feed_forward_length(self.hparams["intermediate_size"]) - self.gguf_writer.add_rope_dimension_count(hidden_size // head_count) + + # NOTE: not sure about this change - why does the model not have a rope dimension count when it is smaller + # than the head size? + # ref: https://github.com/ggerganov/llama.cpp/pull/4889 + #self.gguf_writer.add_rope_dimension_count(hidden_size // head_count) + self.gguf_writer.add_rope_dimension_count(hidden_size // head_count // 2) + self.gguf_writer.add_head_count(head_count) self.gguf_writer.add_head_count_kv(head_count_kv) self.gguf_writer.add_rope_freq_base(self.hparams["rope_theta"]) diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py index 80c1d5449..24a089037 100644 --- a/gguf-py/gguf/tensor_mapping.py +++ b/gguf-py/gguf/tensor_mapping.py @@ -57,6 +57,7 @@ class TensorNameMap: "transformer.norm_f", # mpt "ln_f", # refact bloom qwen gpt2 "language_model.encoder.final_layernorm", # persimmon + "model.final_layernorm", # persimmon "lm_head.ln", # phi2 ), @@ -98,6 +99,7 @@ class TensorNameMap: "transformer.h.{bid}.self_attention.query_key_value", # falcon "h.{bid}.self_attention.query_key_value", # bloom "language_model.encoder.layers.{bid}.self_attention.query_key_value", # persimmon + "model.layers.{bid}.self_attn.query_key_value", # persimmon "h.{bid}.attn.c_attn", # gpt2 "transformer.h.{bid}.mixer.Wqkv", # phi2 ), @@ -141,6 +143,7 @@ class TensorNameMap: "encoder.layer.{bid}.attention.output.dense", # bert "transformer.h.{bid}.attn.out_proj", # gpt-j "language_model.encoder.layers.{bid}.self_attention.dense", # persimmon + "model.layers.{bid}.self_attn.dense", # persimmon "h.{bid}.attn.c_proj", # gpt2 "transformer.h.{bid}.mixer.out_proj", # phi2 "model.layers.layers.{bid}.self_attn.o_proj", # plamo @@ -184,6 +187,7 @@ class TensorNameMap: "encoder.layer.{bid}.intermediate.dense", # bert "transformer.h.{bid}.mlp.fc_in", # gpt-j "language_model.encoder.layers.{bid}.mlp.dense_h_to_4h", # persimmon + "model.layers.{bid}.mlp.dense_h_to_4h", # persimmon "transformer.h.{bid}.mlp.w1", # qwen "h.{bid}.mlp.c_fc", # gpt2 "transformer.h.{bid}.mlp.fc1", # phi2 @@ -225,6 +229,7 @@ class TensorNameMap: "encoder.layer.{bid}.output.dense", # bert "transformer.h.{bid}.mlp.fc_out", # gpt-j "language_model.encoder.layers.{bid}.mlp.dense_4h_to_h", # persimmon + "model.layers.{bid}.mlp.dense_4h_to_h", # persimmon "h.{bid}.mlp.c_proj", # gpt2 "transformer.h.{bid}.mlp.fc2", # phi2 "model.layers.layers.{bid}.mlp.down_proj", # plamo @@ -237,10 +242,12 @@ class TensorNameMap: MODEL_TENSOR.ATTN_Q_NORM: ( "language_model.encoder.layers.{bid}.self_attention.q_layernorm", + "model.layers.{bid}.self_attn.q_layernorm", # persimmon ), MODEL_TENSOR.ATTN_K_NORM: ( "language_model.encoder.layers.{bid}.self_attention.k_layernorm", + "model.layers.{bid}.self_attn.k_layernorm", # persimmon ), MODEL_TENSOR.ROPE_FREQS: ( diff --git a/llama.cpp b/llama.cpp index d39ff94c7..0bab95563 100644 --- a/llama.cpp +++ b/llama.cpp @@ -4104,7 +4104,6 @@ static void llm_build_k_shift( struct ggml_cgraph * graph, llm_rope_type type, int64_t n_ctx, - int n_rot, float freq_base, float freq_scale, const llm_build_cb & cb) { @@ -4112,14 +4111,13 @@ static void llm_build_k_shift( const int64_t n_head_kv = hparams.n_head_kv; const int64_t n_embd_head_k = hparams.n_embd_head_k; const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa(); + const int32_t n_rot = hparams.n_rot; const int32_t n_orig_ctx = cparams.n_yarn_orig_ctx; const float ext_factor = cparams.yarn_ext_factor; const float attn_factor = cparams.yarn_attn_factor; const float beta_fast = cparams.yarn_beta_fast; const float beta_slow = cparams.yarn_beta_slow; - GGML_ASSERT(n_embd_head_k % n_rot == 0); - struct ggml_tensor * K_shift = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, n_ctx); cb(K_shift, "K_shift", -1); @@ -4523,7 +4521,7 @@ struct llm_build_context { // shift the entire K-cache if needed if (do_rope_shift) { - llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE, n_ctx, n_embd_head, freq_base, freq_scale, cb); + llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE, n_ctx, freq_base, freq_scale, cb); } for (int il = 0; il < n_layer; ++il) { @@ -4561,14 +4559,14 @@ struct llm_build_context { Qcur = ggml_rope_custom( ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, - n_embd_head, 0, 0, n_orig_ctx, freq_base, freq_scale, + hparams.n_rot, 0, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); cb(Qcur, "Qcur", il); Kcur = ggml_rope_custom( ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, - n_embd_head, 0, 0, n_orig_ctx, freq_base, freq_scale, + hparams.n_rot, 0, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); cb(Kcur, "Kcur", il); @@ -4691,6 +4689,7 @@ struct llm_build_context { const int64_t n_embd_head = hparams.n_embd_head_v; GGML_ASSERT(n_embd_head == hparams.n_embd_head_k); + GGML_ASSERT(n_embd_head == hparams.n_rot); struct ggml_tensor * cur; struct ggml_tensor * inpL; @@ -4708,7 +4707,7 @@ struct llm_build_context { // shift the entire K-cache if needed if (do_rope_shift) { - llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE, n_ctx, n_embd_head, freq_base, freq_scale, cb); + llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE, n_ctx, freq_base, freq_scale, cb); } for (int il = 0; il < n_layer; ++il) { @@ -4734,12 +4733,12 @@ struct llm_build_context { case MODEL_7B: Qcur = ggml_rope_custom( ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, - n_embd_head, 0, 0, n_orig_ctx, freq_base, freq_scale, + hparams.n_rot, 0, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); Kcur = ggml_rope_custom( ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, - n_embd_head, 0, 0, n_orig_ctx, freq_base, freq_scale, + hparams.n_rot, 0, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); break; @@ -4812,6 +4811,7 @@ struct llm_build_context { const int64_t n_embd_head = hparams.n_embd_head_v; const int64_t n_embd_gqa = hparams.n_embd_v_gqa(); GGML_ASSERT(n_embd_head == hparams.n_embd_head_k); + GGML_ASSERT(n_embd_head == hparams.n_rot); struct ggml_tensor * cur; struct ggml_tensor * inpL; @@ -4829,7 +4829,7 @@ struct llm_build_context { // shift the entire K-cache if needed if (do_rope_shift) { - llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, n_embd_head, freq_base, freq_scale, cb); + llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, freq_base, freq_scale, cb); } for (int il = 0; il < n_layer; ++il) { @@ -4870,13 +4870,13 @@ struct llm_build_context { // using mode = 2 for neox mode Qcur = ggml_rope_custom( - ctx0, Qcur, inp_pos, n_embd_head, 2, 0, n_orig_ctx, + ctx0, Qcur, inp_pos, hparams.n_rot, 2, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); cb(Qcur, "Qcur", il); Kcur = ggml_rope_custom( - ctx0, Kcur, inp_pos, n_embd_head, 2, 0, n_orig_ctx, + ctx0, Kcur, inp_pos, hparams.n_rot, 2, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); cb(Kcur, "Kcur", il); @@ -5033,9 +5033,8 @@ struct llm_build_context { struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false); const int64_t n_embd_head = hparams.n_embd_head_v; - GGML_ASSERT(n_embd_head == hparams.n_embd_head_k); - - const int64_t n_rot = n_embd_head_k / 2; + GGML_ASSERT(n_embd_head == hparams.n_embd_head_k); + GGML_ASSERT(n_embd_head/2 == hparams.n_rot); struct ggml_tensor * cur; struct ggml_tensor * inpL; @@ -5052,7 +5051,7 @@ struct llm_build_context { cb(KQ_mask, "KQ_mask", -1); if (do_rope_shift) { - llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, n_embd_head, freq_base, freq_scale, cb); + llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, freq_base, freq_scale, cb); } for (int il = 0; il < n_layer; ++il) { @@ -5112,7 +5111,7 @@ struct llm_build_context { // RoPE the first n_rot of q/k, pass the other half, and concat. struct ggml_tensor * qrot = ggml_view_3d( - ctx0, tmpq, n_rot, n_head, n_tokens, + ctx0, tmpq, hparams.n_rot, n_head, n_tokens, ggml_element_size(tmpq) * n_embd_head, ggml_element_size(tmpq) * n_embd_head * n_head, 0 @@ -5120,7 +5119,7 @@ struct llm_build_context { cb(qrot, "qrot", il); struct ggml_tensor * krot = ggml_view_3d( - ctx0, tmpk, n_rot, n_head, n_tokens, + ctx0, tmpk, hparams.n_rot, n_head, n_tokens, ggml_element_size(tmpk) * n_embd_head, ggml_element_size(tmpk) * n_embd_head * n_head, 0 @@ -5129,29 +5128,29 @@ struct llm_build_context { // get the second half of tmpq, e.g tmpq[n_rot:, :, :] struct ggml_tensor * qpass = ggml_view_3d( - ctx0, tmpq, n_rot, n_head, n_tokens, + ctx0, tmpq, hparams.n_rot, n_head, n_tokens, ggml_element_size(tmpq) * n_embd_head, ggml_element_size(tmpq) * n_embd_head * n_head, - ggml_element_size(tmpq) * n_rot + ggml_element_size(tmpq) * hparams.n_rot ); cb(qpass, "qpass", il); struct ggml_tensor * kpass = ggml_view_3d( - ctx0, tmpk, n_rot, n_head, n_tokens, + ctx0, tmpk, hparams.n_rot, n_head, n_tokens, ggml_element_size(tmpk) * n_embd_head, ggml_element_size(tmpk) * n_embd_head * n_head, - ggml_element_size(tmpk) * n_rot + ggml_element_size(tmpk) * hparams.n_rot ); cb(kpass, "kpass", il); struct ggml_tensor * qrotated = ggml_rope_custom( - ctx0, qrot, inp_pos, n_rot, 2, 0, n_orig_ctx, + ctx0, qrot, inp_pos, hparams.n_rot, 2, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); cb(qrotated, "qrotated", il); struct ggml_tensor * krotated = ggml_rope_custom( - ctx0, krot, inp_pos, n_rot, 2, 0, n_orig_ctx, + ctx0, krot, inp_pos, hparams.n_rot, 2, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); cb(krotated, "krotated", il); @@ -5531,6 +5530,7 @@ struct llm_build_context { const int64_t n_embd_head = hparams.n_embd_head_v; GGML_ASSERT(n_embd_head == hparams.n_embd_head_k); + GGML_ASSERT(n_embd_head == hparams.n_rot); struct ggml_tensor * cur; struct ggml_tensor * inpL; @@ -5548,7 +5548,7 @@ struct llm_build_context { // shift the entire K-cache if needed if (do_rope_shift) { - llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, hparams.n_rot, freq_base, freq_scale, cb); + llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, freq_base, freq_scale, cb); } for (int il = 0; il < n_layer; ++il) { @@ -5661,7 +5661,7 @@ struct llm_build_context { // shift the entire K-cache if needed if (do_rope_shift) { - llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, n_embd_head, freq_base, freq_scale, cb); + llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, freq_base, freq_scale, cb); } for (int il = 0; il < n_layer; ++il) { @@ -5693,13 +5693,13 @@ struct llm_build_context { // using mode = 2 for neox mode Qcur = ggml_rope_custom( - ctx0, Qcur, inp_pos, n_embd_head, 2, 0, n_orig_ctx, + ctx0, Qcur, inp_pos, hparams.n_rot, 2, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); cb(Qcur, "Qcur", il); Kcur = ggml_rope_custom( - ctx0, Kcur, inp_pos, n_embd_head, 2, 0, n_orig_ctx, + ctx0, Kcur, inp_pos, hparams.n_rot, 2, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow ); cb(Kcur, "Kcur", il); @@ -5778,7 +5778,7 @@ struct llm_build_context { // shift the entire K-cache if needed if (do_rope_shift) { - llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, n_embd_head, freq_base, freq_scale, cb); + llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE_NEOX, n_ctx, freq_base, freq_scale, cb); } for (int il = 0; il < n_layer; ++il) { @@ -5874,6 +5874,7 @@ struct llm_build_context { const int64_t n_embd_head = hparams.n_embd_head_v; GGML_ASSERT(n_embd_head == hparams.n_embd_head_k); + GGML_ASSERT(n_embd_head == hparams.n_rot); struct ggml_tensor * cur; struct ggml_tensor * inpL; @@ -5891,7 +5892,7 @@ struct llm_build_context { // shift the entire K-cache if needed if (do_rope_shift) { - llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE, n_ctx, n_embd_head, freq_base, freq_scale, cb); + llm_build_k_shift(ctx0, hparams, cparams, kv_self, gf, LLM_ROPE, n_ctx, freq_base, freq_scale, cb); } for (int il = 0; il < n_layer; ++il) { @@ -5917,13 +5918,13 @@ struct llm_build_context { cb(Vcur, "Vcur", il); Qcur = ggml_rope_custom( - ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, + ctx0, ggml_reshape_3d(ctx0, Qcur, hparams.n_rot, n_head, n_tokens), inp_pos, n_embd_head, 2, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow); cb(Qcur, "Qcur", il); Kcur = ggml_rope_custom( - ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, + ctx0, ggml_reshape_3d(ctx0, Kcur, hparams.n_rot, n_head_kv, n_tokens), inp_pos, n_embd_head, 2, 0, n_orig_ctx, freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow); cb(Kcur, "Kcur", il);