Fix log_* formats which expect size_t but receive uint32_t.

src/address_dictionary.c

@@ -15,7 +15,7 @@ address_dictionary_t *get_address_dictionary(void) {
 
 address_expansion_value_t *address_dictionary_get_expansions(uint32_t i) {
     if (address_dict == NULL || address_dict->values == NULL || i > address_dict->values->n) {
-        log_error("i=%zu, address_dict->values->n=%zu\n", i, address_dict->values->n);
+        log_error("i=%" PRIu32 ", address_dict->values->n=%zu\n", i, address_dict->values->n);
         log_error(ADDRESS_DICTIONARY_SETUP_ERROR);
         return NULL;
     }

src/ftrl.c

@@ -243,7 +243,7 @@ sparse_matrix_t *ftrl_weights_finalize_sparse(ftrl_trainer_t *self) {
     double lambda2 = self->lambda2;
 
     sparse_matrix_t *weights = sparse_matrix_new();
-    log_info("weights->m = %zu\n", weights->m);
+    log_info("weights->m = %" PRIu32 "\n", weights->m);
 
     size_t i_start = 0;
 
@@ -259,7 +259,7 @@ sparse_matrix_t *ftrl_weights_finalize_sparse(ftrl_trainer_t *self) {
         sparse_matrix_finalize_row(weights);
         i_start = 1;
     }
-    log_info("after intercept weights->m = %zu\n", weights->m);
+    log_info("after intercept weights->m = %" PRIu32 "\n", weights->m);
 
     for (size_t i = i_start; i < m; i++) {
         double *row = double_matrix_get_row(self->z, (size_t)i);
@@ -275,7 +275,7 @@ sparse_matrix_t *ftrl_weights_finalize_sparse(ftrl_trainer_t *self) {
         sparse_matrix_finalize_row(weights);
 
         if (i % 1000 == 0 && i > 0) {
-            log_info("adding rows, weights->m = %zu\n", weights->m);
+            log_info("adding rows, weights->m = %" PRIu32 "\n", weights->m);
         }
     }
 

src/language_classifier_test.c

@@ -53,7 +53,7 @@ double test_accuracy(char *filename) {
 
     }
 
-    log_info("total=%zu\n", total);
+    log_info("total=%" PRIu32 "\n", total);
 
     trie_destroy(label_ids);
 

src/language_classifier_train.c

@@ -599,13 +599,13 @@ static language_classifier_t *trainer_finalize(logistic_regression_trainer_t *tr
             sparse_matrix_t *sparse_weights = logistic_regression_trainer_final_weights_sparse(trainer);
             classifier->weights_type = MATRIX_SPARSE;
             classifier->weights.sparse = sparse_weights;
-            log_info("Weights sparse: %zu rows (m=%u), %zu cols, %zu elements\n", sparse_weights->indptr->n, sparse_weights->m, sparse_weights->n, sparse_weights->data->n);
+            log_info("Weights sparse: %zu rows (m=%u), %" PRIu32 " cols, %zu elements\n", sparse_weights->indptr->n, sparse_weights->m, sparse_weights->n, sparse_weights->data->n);
         }
     } else if (trainer->optimizer_type == LOGISTIC_REGRESSION_OPTIMIZER_FTRL) {
         sparse_matrix_t *sparse_weights = logistic_regression_trainer_final_weights_sparse(trainer);
         classifier->weights_type = MATRIX_SPARSE;
         classifier->weights.sparse = sparse_weights;
-        log_info("Weights sparse: %zu rows (m=%u), %zu cols, %zu elements\n", sparse_weights->indptr->n, sparse_weights->m, sparse_weights->n, sparse_weights->data->n);
+        log_info("Weights sparse: %zu rows (m=%u), %" PRIu32 " cols, %zu elements\n", sparse_weights->indptr->n, sparse_weights->m, sparse_weights->n, sparse_weights->data->n);
     }
 
 

src/libpostal.c

@@ -665,7 +665,7 @@ static bool add_affix_expansions(string_tree_t *tree, char *str, char *lang, tok
 
         }
     } else if (have_suffix) {
-        log_debug("suffix.start=%zu\n", suffix.start);
+        log_debug("suffix.start=%" PRId32 "\n", suffix.start);
         root_len = suffix.start;
         root_token = (token_t){token.offset, root_len, token.type};
         log_debug("root_len=%zu\n", root_len);
@@ -887,7 +887,7 @@ static void expand_alternative(cstring_array *strings, khash_t(str_set) *unique_
         log_debug("Adding alternatives for single normalization\n");
         alternatives = add_string_alternatives(tokenized_str, options);
 
-        log_debug("num strings = %zu\n", string_tree_num_strings(alternatives));
+        log_debug("num strings = %" PRIu32 "\n", string_tree_num_strings(alternatives));
 
         if (alternatives == NULL) {
             log_debug("alternatives = NULL\n");

src/log/log.h

@@ -3,6 +3,7 @@
 
 #include <stdio.h>
 #include <errno.h>
+#include <inttypes.h>
 #include <string.h>
 
 #define LOG_LEVEL_DEBUG 10

src/logistic_regression.c

@@ -13,7 +13,7 @@ bool logistic_regression_model_expectation_sparse(sparse_matrix_t *theta, sparse
     }
 
     if (sparse_matrix_dot_sparse(x, theta, p_y) != 0) {
-        log_error("x->m = %zu, x->n = %zu, theta->m = %zu, theta->n = %zu, p_y->m = %zu, p_y->n = %zu\n", x->m, x->n, theta->m, theta->n, p_y->m, p_y->n);
+        log_error("x->m = %" PRIu32 ", x->n = %" PRIu32 ", theta->m = %" PRIu32 ", theta->n = %" PRIu32 ", p_y->m = %zu, p_y->n = %zu\n", x->m, x->n, theta->m, theta->n, p_y->m, p_y->n);
         return false;
     }
 
@@ -31,7 +31,7 @@ bool logistic_regression_model_expectation(double_matrix_t *theta, sparse_matrix
     }
 
     if (sparse_matrix_dot_dense(x, theta, p_y) != 0) {
-        log_error("x->m = %zu, x->n = %zu, theta->m = %zu, theta->n = %zu, p_y->m = %zu, p_y->n = %zu\n", x->m, x->n, theta->m, theta->n, p_y->m, p_y->n);
+        log_error("x->m = %" PRIu32 ", x->n = %" PRIu32 ", theta->m = %" PRIu32 ", theta->n = %" PRIu32 ", p_y->m = %zu, p_y->n = %zu\n", x->m, x->n, theta->m, theta->n, p_y->m, p_y->n);
         return false;
     }
 

src/stochastic_gradient_descent.c

@@ -203,7 +203,7 @@ bool stochastic_gradient_descent_update_sparse(sgd_trainer_t *self, double_matri
         lambda_update = lambda / (double)batch_size * gamma_t;
 
         if (t > self->penalties->n) {
-            log_info("t = %zu, penalties->n = %zu\n", t, self->penalties->n);
+            log_info("t = %" PRIu32 ", penalties->n = %zu\n", t, self->penalties->n);
             return false;
         }
         penalty = self->penalties->a[t];
@@ -219,7 +219,7 @@ bool stochastic_gradient_descent_update_sparse(sgd_trainer_t *self, double_matri
 
         if (self->iterations > 0) {
             if (last_updated >= self->penalties->n) {
-                log_info("col = %u, t = %zu, last_updated = %zu, penalties->n = %zu\n", col, t, last_updated, self->penalties->n);
+                log_info("col = %u, t = %" PRIu32 ", last_updated = %" PRIu32 ", penalties->n = %zu\n", col, t, last_updated, self->penalties->n);
                 return false;
             }
 
@@ -376,7 +376,7 @@ bool stochastic_gradient_descent_set_regularized_weights(sgd_trainer_t *self, do
 
             uint32_t last_updated = updates[i];
             if (last_updated >= self->penalties->n) {
-                log_error("last_updated (%zu) >= self->penalties-> (%zu)\n", last_updated, self->penalties->n);
+                log_error("last_updated (%" PRIu32 ") >= self->penalties-> (%zu)\n", last_updated, self->penalties->n);
                 return false;
             }
             double last_update_penalty = penalties[last_updated];