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fix: model loading

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This commit is contained in:
Zach Nussbaum 2023-05-07 18:18:22 -04:00 committed by Adam Treat
parent f732ba2d56
commit d30be81506
1 changed files with 22 additions and 16 deletions
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38
llmodel/mpt.cpp
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@ -26,7 +26,7 @@ struct mpt_hparams {
int32_t n_head = 32; int32_t n_head = 32;
int32_t n_layer = 32; int32_t n_layer = 32;
// this isn't used should we remove? // this isn't used should we remove?
int32_t n_rot = 64; int32_t n_rot = 0;
int32_t f16 = 1; int32_t f16 = 1;
}; };
@ -162,7 +162,7 @@ bool mpt_model_load(const std::string &fname, std::istream &fin, mpt_model & mod
{ {
uint32_t magic; uint32_t magic;
fin.read((char *) &magic, sizeof(magic)); fin.read((char *) &magic, sizeof(magic));
if (magic != 0x67676d6c) { if (magic != 0x67676d6d) {
fprintf(stderr, "%s: invalid model file '%s' (bad magic)\n", __func__, fname.c_str()); fprintf(stderr, "%s: invalid model file '%s' (bad magic)\n", __func__, fname.c_str());
return false; return false;
} }
@ -268,6 +268,9 @@ bool mpt_model_load(const std::string &fname, std::istream &fin, mpt_model & mod
ctx_size += n_ctx*n_layer*n_embd*ggml_type_sizef(GGML_TYPE_F32); // memory_k ctx_size += n_ctx*n_layer*n_embd*ggml_type_sizef(GGML_TYPE_F32); // memory_k
ctx_size += n_ctx*n_layer*n_embd*ggml_type_sizef(GGML_TYPE_F32); // memory_v ctx_size += n_ctx*n_layer*n_embd*ggml_type_sizef(GGML_TYPE_F32); // memory_v
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_2_g
ctx_size += n_layer*(n_embd*ggml_type_sizef(GGML_TYPE_F32)); // ln_2_b
// TODO: what is this?? // TODO: what is this??
ctx_size += (5 + 10*n_layer)*256; // object overhead ctx_size += (5 + 10*n_layer)*256; // object overhead
@ -335,23 +338,23 @@ bool mpt_model_load(const std::string &fname, std::istream &fin, mpt_model & mod
layer.down_proj_b = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_embd); layer.down_proj_b = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_embd);
// map by name // map by name
model.tensors["transformer.block." + std::to_string(i) + ".norm_1.weight"] = layer.norm_1_g; model.tensors["transformer.blocks." + std::to_string(i) + ".norm_1.weight"] = layer.norm_1_g;
model.tensors["transformer.block." + std::to_string(i) + ".norm_1.bias"] = layer.norm_1_b; model.tensors["transformer.blocks." + std::to_string(i) + ".norm_1.bias"] = layer.norm_1_b;
model.tensors["transformer.block." + std::to_string(i) + ".attn.q_proj.weight"] = layer.c_attn_q_proj_w; model.tensors["transformer.blocks." + std::to_string(i) + ".attn.q_proj.weight"] = layer.c_attn_q_proj_w;
model.tensors["transformer.block." + std::to_string(i) + ".attn.k_proj.weight"] = layer.c_attn_k_proj_w; model.tensors["transformer.blocks." + std::to_string(i) + ".attn.k_proj.weight"] = layer.c_attn_k_proj_w;
model.tensors["transformer.block." + std::to_string(i) + ".attn.v_proj.weight"] = layer.c_attn_v_proj_w; model.tensors["transformer.blocks." + std::to_string(i) + ".attn.v_proj.weight"] = layer.c_attn_v_proj_w;
model.tensors["transformer.block." + std::to_string(i) + ".attn.out_proj.weight"] = layer.c_attn_proj_w; model.tensors["transformer.blocks." + std::to_string(i) + ".attn.out_proj.weight"] = layer.c_attn_proj_w;
model.tensors["transformer.block." + std::to_string(i) + ".mlp.up_proj.weight"] = layer.up_proj_w; model.tensors["transformer.blocks." + std::to_string(i) + ".ffn.up_proj.weight"] = layer.up_proj_w;
model.tensors["transformer.block." + std::to_string(i) + ".mlp.up_proj.bias"] = layer.up_proj_b; model.tensors["transformer.blocks." + std::to_string(i) + ".ffn.up_proj.bias"] = layer.up_proj_b;
model.tensors["transformer.block." + std::to_string(i) + ".mlp.down_proj.weight"] = layer.down_proj_w; model.tensors["transformer.blocks." + std::to_string(i) + ".ffn.down_proj.weight"] = layer.down_proj_w;
model.tensors["transformer.block." + std::to_string(i) + ".mlp.down_proj.bias"] = layer.down_proj_b; model.tensors["transformer.blocks." + std::to_string(i) + ".ffn.down_proj.bias"] = layer.down_proj_b;
model.tensors["transformer.block." + std::to_string(i) + ".norm_2.weight"] = layer.norm_2_g; model.tensors["transformer.blocks." + std::to_string(i) + ".norm_2.weight"] = layer.norm_2_g;
model.tensors["transformer.block." + std::to_string(i) + ".norm_2.bias"] = layer.norm_2_b; model.tensors["transformer.blocks." + std::to_string(i) + ".norm_2.bias"] = layer.norm_2_b;
} }
// key + value memory // key + value memory
@ -390,6 +393,8 @@ bool mpt_model_load(const std::string &fname, std::istream &fin, mpt_model & mod
fin.read(reinterpret_cast<char *>(&length), sizeof(length)); fin.read(reinterpret_cast<char *>(&length), sizeof(length));
fin.read(reinterpret_cast<char *>(&ftype), sizeof(ftype)); fin.read(reinterpret_cast<char *>(&ftype), sizeof(ftype));
fprintf(stderr, "%s: n_dims = %d, length = %d, ftype = %d\n", __func__, n_dims, length, ftype);
if (fin.eof()) { if (fin.eof()) {
break; break;
} }
@ -403,7 +408,7 @@ bool mpt_model_load(const std::string &fname, std::istream &fin, mpt_model & mod
std::string name(length, 0); std::string name(length, 0);
fin.read(&name[0], length); fin.read(&name[0], length);
fprintf(stderr, "%s: %s\n", __func__, name.data());
if (model.tensors.find(name.data()) == model.tensors.end()) { if (model.tensors.find(name.data()) == model.tensors.end()) {
fprintf(stderr, "%s: unknown tensor '%s' in model file\n", __func__, name.data()); fprintf(stderr, "%s: unknown tensor '%s' in model file\n", __func__, name.data());
return false; return false;
@ -448,7 +453,8 @@ bool mpt_model_load(const std::string &fname, std::istream &fin, mpt_model & mod
fin.read(reinterpret_cast<char *>(tensor->data), ggml_nbytes(tensor)); fin.read(reinterpret_cast<char *>(tensor->data), ggml_nbytes(tensor));
//printf("%42s - [%5d, %5d], type = %6s, %6.2f MB\n", name.data(), ne[0], ne[1], ftype == 0 ? "float" : "f16", ggml_nbytes(tensor)/1024.0/1024.0);
fprintf(stderr, "%42s - [%5d, %5d], type = %6s, %6.2f MB\n", name.data(), ne[0], ne[1], ftype == 0 ? "float" : "f16", ggml_nbytes(tensor)/1024.0/1024.0);
total_size += ggml_nbytes(tensor); total_size += ggml_nbytes(tensor);
if (++n_tensors % 8 == 0) { if (++n_tensors % 8 == 0) {
printf("."); printf(".");