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@@ -12176,18 +12176,19 @@ static void llama_copy_state_data_internal(struct llama_context * ctx, llama_dat
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data_ctx->write(&kv_used, sizeof(kv_used));
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data_ctx->write(&kv_used, sizeof(kv_used));
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if (kv_buf_size) {
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if (kv_buf_size) {
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- const size_t elt_size = ggml_element_size(kv_self.k_l[0]);
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-
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std::vector<uint8_t> tmp_buf;
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std::vector<uint8_t> tmp_buf;
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for (int il = 0; il < (int) n_layer; ++il) {
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for (int il = 0; il < (int) n_layer; ++il) {
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- tmp_buf.resize(elt_size*n_embd_k_gqa*kv_head);
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+ size_t k_size = ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*kv_head);
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+ tmp_buf.resize(k_size);
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ggml_backend_tensor_get(kv_self.k_l[il], tmp_buf.data(), 0, tmp_buf.size());
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ggml_backend_tensor_get(kv_self.k_l[il], tmp_buf.data(), 0, tmp_buf.size());
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data_ctx->write(tmp_buf.data(), tmp_buf.size());
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data_ctx->write(tmp_buf.data(), tmp_buf.size());
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// v is not contiguous, copy row by row
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// v is not contiguous, copy row by row
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- tmp_buf.resize(elt_size*kv_head);
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+ size_t v_row_size = ggml_row_size(kv_self.v_l[il]->type, kv_head);
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+ size_t v_row_stride = ggml_row_size(kv_self.v_l[il]->type, n_ctx);
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+ tmp_buf.resize(v_row_size);
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for (int ir = 0; ir < (int) n_embd_v_gqa; ++ir) {
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for (int ir = 0; ir < (int) n_embd_v_gqa; ++ir) {
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- ggml_backend_tensor_get(kv_self.v_l[il], tmp_buf.data(), ir*elt_size*n_ctx, tmp_buf.size());
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+ ggml_backend_tensor_get(kv_self.v_l[il], tmp_buf.data(), ir*v_row_stride, tmp_buf.size());
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data_ctx->write(tmp_buf.data(), tmp_buf.size());
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data_ctx->write(tmp_buf.data(), tmp_buf.size());
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}
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}
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}
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}
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@@ -12289,17 +12290,16 @@ size_t llama_set_state_data(struct llama_context * ctx, uint8_t * src) {
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if (kv_buf_size) {
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if (kv_buf_size) {
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GGML_ASSERT(kv_self.total_size() == kv_buf_size);
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GGML_ASSERT(kv_self.total_size() == kv_buf_size);
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- const size_t elt_size = ggml_element_size(kv_self.k_l[0]);
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-
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for (int il = 0; il < (int) n_layer; ++il) {
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for (int il = 0; il < (int) n_layer; ++il) {
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- size_t k_size = elt_size*n_embd_k_gqa*kv_head;
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+ size_t k_size = ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*kv_head);
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ggml_backend_tensor_set(kv_self.k_l[il], inp, 0, k_size);
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ggml_backend_tensor_set(kv_self.k_l[il], inp, 0, k_size);
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inp += k_size;
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inp += k_size;
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// v is not contiguous, copy row by row
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// v is not contiguous, copy row by row
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- size_t v_row_size = elt_size*kv_head;
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+ size_t v_row_size = ggml_row_size(kv_self.v_l[il]->type, kv_head);
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+ size_t v_row_stride = ggml_row_size(kv_self.v_l[il]->type, n_ctx);
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for (int ir = 0; ir < (int) n_embd_v_gqa; ++ir) {
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for (int ir = 0; ir < (int) n_embd_v_gqa; ++ir) {
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- ggml_backend_tensor_set(kv_self.v_l[il], inp, ir*elt_size*n_ctx, v_row_size);
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+ ggml_backend_tensor_set(kv_self.v_l[il], inp, ir*v_row_stride, v_row_size);
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inp += v_row_size;
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inp += v_row_size;
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}
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}
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}
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}
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