context : remove logits_all flag

ggml-ci

common/arg.cpp

@@ -2097,13 +2097,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.cache_type_v = kv_cache_type_from_str(value);
         }
     ).set_env("LLAMA_ARG_CACHE_TYPE_V"));
-    add_opt(common_arg(
-        {"--perplexity", "--all-logits"},
-        string_format("return logits for all tokens in the batch (default: %s)", params.logits_all ? "true" : "false"),
-        [](common_params & params) {
-            params.logits_all = true;
-        }
-    ).set_examples({LLAMA_EXAMPLE_PERPLEXITY}));
     add_opt(common_arg(
         {"--hellaswag"},
         "compute HellaSwag score over random tasks from datafile supplied with -f",

common/common.cpp

@@ -1096,7 +1096,7 @@ struct llama_context_params common_context_params_to_llama(const common_params &
     cparams.n_threads         = params.cpuparams.n_threads;
     cparams.n_threads_batch   = params.cpuparams_batch.n_threads == -1 ?
                                 params.cpuparams.n_threads : params.cpuparams_batch.n_threads;
-    cparams.logits_all        = params.logits_all;
+    cparams.logits_all        = false;
     cparams.embeddings        = params.embedding;
     cparams.rope_scaling_type = params.rope_scaling_type;
     cparams.rope_freq_base    = params.rope_freq_base;

common/common.h

@@ -324,7 +324,6 @@ struct common_params {
     bool ctx_shift         = true;  // context shift on inifinite text generation
 
     bool input_prefix_bos  = false; // prefix BOS to user inputs, preceding input_prefix
-    bool logits_all        = false; // return logits for all tokens in the batch
     bool use_mmap          = true;  // use mmap for faster loads
     bool use_mlock         = false; // use mlock to keep model in memory
     bool verbose_prompt    = false; // print prompt tokens before generation

src/llama-context.cpp

@@ -116,8 +116,6 @@ llama_context::llama_context(
                 __func__, n_ctx_per_seq, hparams.n_ctx_train);
     }
 
-    logits_all = params.logits_all;
-
     if (!hparams.vocab_only) {
         // GPU backends
         for (auto * dev : model.devices) {
@@ -890,7 +888,7 @@ int llama_context::decode(llama_batch & inp_batch) {
         for (uint32_t i = 0; i < n_tokens_all; ++i) {
             n_outputs_all += batch.logits[i] != 0;
         }
-    } else if (logits_all || embd_pooled) {
+    } else if (embd_pooled) {
         n_outputs_all = n_tokens_all;
     } else {
         // keep last output only

src/llama-context.h

@@ -187,9 +187,6 @@ struct llama_context {
 
     std::unique_ptr<llama_memory_i> memory;
 
-    // TODO: remove
-    bool logits_all = false;
-
     // decode output (2-dimensional array: [n_outputs][n_vocab])
     size_t  logits_size = 0; // capacity (of floats) for logits
     float * logits      = nullptr;

tools/imatrix/imatrix.cpp

@@ -585,7 +585,6 @@ int main(int argc, char ** argv) {
     params.out_file = "imatrix.dat" ;
 
     params.n_ctx = 512;
-    params.logits_all = true;
     params.escape = false;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_IMATRIX, print_usage)) {

tools/main/main.cpp

@@ -99,14 +99,6 @@ int main(int argc, char ** argv) {
     console::init(params.simple_io, params.use_color);
     atexit([]() { console::cleanup(); });
 
-    if (params.logits_all) {
-        LOG_ERR("************\n");
-        LOG_ERR("%s: please use the 'perplexity' tool for perplexity calculations\n", __func__);
-        LOG_ERR("************\n\n");
-
-        return 0;
-    }
-
     if (params.embedding) {
         LOG_ERR("************\n");
         LOG_ERR("%s: please use the 'embedding' tool for embedding calculations\n", __func__);

tools/perplexity/perplexity.cpp

@@ -1554,7 +1554,10 @@ static void multiple_choice_score(llama_context * ctx, const common_params & par
             if (int(batch_indeces.size()) != num_answers) {
                 batch_indeces.resize(num_answers);
             }
-            for (int s = 0; s < num_answers; ++s) batch_indeces[s] = s0 + s;
+
+            for (int s = 0; s < num_answers; ++s) {
+                batch_indeces[s] = s0 + s;
+            }
 
             for (size_t i = 0; i < cur_task.common_prefix; ++i) {
                 //llama_batch_add(batch, cur_task.seq_tokens[0][i], i, { s0 + 0, s0 + 1, s0 + 2, s0 + 3}, false);
@@ -1970,7 +1973,6 @@ int main(int argc, char ** argv) {
     common_params params;
 
     params.n_ctx = 512;
-    params.logits_all = true;
     params.escape = false;
 
     if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_PERPLEXITY)) {