context : minor cleanup

ggml-ci

Author: ggerganov

src/llama-context.cpp

@@ -10,30 +10,6 @@
 #include <stdexcept>
 #include <cinttypes>
 
-static int32_t llama_relative_position_bucket(llama_pos x, llama_pos y, uint64_t n_buckets, bool bidirectional) {
-    // TODO move to hparams if a T5 variant appears that uses a different value
-    const int64_t max_distance = 128;
-
-    if (bidirectional) {
-        n_buckets >>= 1;
-    }
-
-    const int64_t max_exact = n_buckets >> 1;
-
-    int32_t relative_position = x - y;
-    int32_t relative_bucket = 0;
-    if (bidirectional) {
-        relative_bucket += (relative_position > 0) * n_buckets;
-        relative_position = abs(relative_position);
-    } else {
-        relative_position = -std::min<int32_t>(relative_position, 0);
-    }
-    int32_t relative_position_if_large = floorf(max_exact + logf(1.0 * relative_position / max_exact) * (n_buckets - max_exact) / log(1.0 * max_distance / max_exact));
-    relative_position_if_large = std::min<int32_t>(relative_position_if_large, n_buckets - 1);
-    relative_bucket += (relative_position < max_exact ? relative_position : relative_position_if_large);
-    return relative_bucket;
-}
-
 //
 // llama_context
 //
@@ -346,6 +322,7 @@ class llama_io_write_dummy : public llama_io_write_i {
         return size_written;
     }
 
+private:
     size_t size_written = 0;
 };
 
@@ -378,6 +355,7 @@ class llama_io_write_buffer : public llama_io_write_i {
         return size_written;
     }
 
+private:
     uint8_t * ptr;
     size_t buf_size = 0;
     size_t size_written = 0;
@@ -406,6 +384,7 @@ class llama_io_read_buffer : public llama_io_read_i {
         return size_read;
     }
 
+private:
     const uint8_t * ptr;
     size_t buf_size = 0;
     size_t size_read = 0;
@@ -430,6 +409,7 @@ class llama_io_write_file : public llama_io_write_i {
         return size_written;
     }
 
+private:
     llama_file * file;
     size_t size_written = 0;
     std::vector<uint8_t> temp_buffer;
@@ -454,6 +434,7 @@ class llama_io_read_file : public llama_io_read_i {
         return size_read;
     }
 
+private:
     llama_file * file;
     size_t size_read = 0;
     std::vector<uint8_t> temp_buffer;
@@ -2132,22 +2113,46 @@ void llama_context_kv_self::set_inputs(const llama_ubatch & ubatch) {
         GGML_ASSERT(ggml_backend_buffer_is_host(inp_pos_bucket->buffer));
         GGML_ASSERT(!ubatch.equal_seqs); // TODO: use ubatch.n_seqs instead of failing
 
+        static const auto relative_position_bucket = [](llama_pos x, llama_pos y, uint64_t n_buckets, bool bidirectional) {
+            // TODO move to hparams if a T5 variant appears that uses a different value
+            const int64_t max_distance = 128;
+
+            if (bidirectional) {
+                n_buckets >>= 1;
+            }
+
+            const int64_t max_exact = n_buckets >> 1;
+
+            int32_t relative_position = x - y;
+            int32_t relative_bucket = 0;
+            if (bidirectional) {
+                relative_bucket += (relative_position > 0) * n_buckets;
+                relative_position = abs(relative_position);
+            } else {
+                relative_position = -std::min<int32_t>(relative_position, 0);
+            }
+            int32_t relative_position_if_large = floorf(max_exact + logf(1.0 * relative_position / max_exact) * (n_buckets - max_exact) / log(1.0 * max_distance / max_exact));
+            relative_position_if_large = std::min<int32_t>(relative_position_if_large, n_buckets - 1);
+            relative_bucket += (relative_position < max_exact ? relative_position : relative_position_if_large);
+            return relative_bucket;
+        };
+
         int32_t * data = (int32_t *) inp_pos_bucket->data;
 
         if (!is_encoding) {
             const int64_t n_kv = kv_self.n;
             for (int h = 0; h < 1; ++h) {
                 for (int j = 0; j < n_tokens; ++j) {
                     for (int i = 0; i < n_kv; ++i) {
-                        data[h*(n_kv*n_tokens) + j*n_kv + i] = llama_relative_position_bucket(kv_self.cells[i].pos, ubatch.pos[j], hparams.n_rel_attn_bkts, is_encoding);
+                        data[h*(n_kv*n_tokens) + j*n_kv + i] = relative_position_bucket(kv_self.cells[i].pos, ubatch.pos[j], hparams.n_rel_attn_bkts, is_encoding);
                     }
                 }
             }
         } else {
             for (int h = 0; h < 1; ++h) {
                 for (int j = 0; j < n_tokens; ++j) {
                     for (int i = 0; i < n_tokens; ++i) {
-                        data[h*(n_tokens*n_tokens) + j*n_tokens + i] = llama_relative_position_bucket(ubatch.pos[i], ubatch.pos[j], hparams.n_rel_attn_bkts, is_encoding);
+                        data[h*(n_tokens*n_tokens) + j*n_tokens + i] = relative_position_bucket(ubatch.pos[i], ubatch.pos[j], hparams.n_rel_attn_bkts, is_encoding);
                     }
                 }
             }