context : move encode/decode to llama-context.cpp

Author: ggerganov

src/llama-context.cpp

@@ -3980,6 +3980,31 @@ size_t llama_state_seq_load_file(struct llama_context * ctx, const char * filepa
     }
 }
 
+///
+
+int32_t llama_encode(
+        struct llama_context * ctx,
+          struct llama_batch   batch) {
+    const int ret = ctx->encode(batch);
+    if (ret != 0) {
+        LLAMA_LOG_ERROR("%s: failed to encode, ret = %d\n", __func__, ret);
+    }
+
+    return ret;
+}
+
+int32_t llama_decode(
+        struct llama_context * ctx,
+          struct llama_batch   batch) {
+    const int ret = ctx->decode(batch);
+    if (ret != 0) {
+        LLAMA_LOG_ERROR("%s: failed to decode, ret = %d\n", __func__, ret);
+    }
+
+    return ret;
+}
+
+
 const std::vector<std::pair<std::string, struct ggml_tensor *>> & llama_internal_get_tensor_map(
     struct llama_context * ctx
 ) {

src/llama-context.h

@@ -45,7 +45,30 @@ struct llama_context {
 
     virtual ggml_context_ptr init();
 
+    // decode a batch of tokens by evaluating the transformer
+    // in case of unsuccessful decoding (error or warning),
+    // the kv_cache state will be returned to its original state
+    // (for non-recurrent models) or cleaned (for recurrent models)
+    //
+    //   - lctx:      llama context
+    //   - inp_batch: batch to evaluate
+    //
+    // return 0 on success
+    // return positive int on warning
+    // return negative int on error
+    //
     virtual int decode(llama_batch & inp_batch) = 0;
+
+
+    // encode a batch of tokens by evaluating the encoder part of the transformer
+    //
+    //   - lctx:      llama context
+    //   - batch:     batch to evaluate
+    //
+    // return 0 on success
+    // return positive int on warning
+    // return negative int on error
+    //
     virtual int encode(llama_batch & inp_batch) = 0;
 
     // graph build API (generic)

src/llama.cpp

@@ -7401,39 +7401,6 @@ static struct ggml_cgraph * llama_build_graph(
     return result;
 }
 
-// decode a batch of tokens by evaluating the transformer
-// in case of unsuccessful decoding (error or warning),
-// the kv_cache state will be returned to its original state
-// (for non-recurrent models) or cleaned (for recurrent models)
-//
-//   - lctx:      llama context
-//   - inp_batch: batch to evaluate
-//
-// return 0 on success
-// return positive int on warning
-// return negative int on error
-//
-static int llama_decode_impl(
-         llama_context & lctx,
-           llama_batch   inp_batch) {
-    return lctx.decode(inp_batch);
-}
-
-// encode a batch of tokens by evaluating the encoder part of the transformer
-//
-//   - lctx:      llama context
-//   - batch:     batch to evaluate
-//
-// return 0 on success
-// return positive int on warning
-// return negative int on error
-//
-static int llama_encode_impl(
-         llama_context & lctx,
-           llama_batch   inp_batch) {
-    return lctx.encode(inp_batch);
-}
-
 //
 // interface implementation
 //
@@ -7759,30 +7726,6 @@ struct llama_context * llama_new_context_with_model(
     return llama_init_from_model(model, params);
 }
 
-///
-
-int32_t llama_encode(
-        struct llama_context * ctx,
-          struct llama_batch   batch) {
-    const int ret = llama_encode_impl(*ctx, batch);
-    if (ret != 0) {
-        LLAMA_LOG_ERROR("%s: failed to encode, ret = %d\n", __func__, ret);
-    }
-
-    return ret;
-}
-
-int32_t llama_decode(
-        struct llama_context * ctx,
-          struct llama_batch   batch) {
-    const int ret = llama_decode_impl(*ctx, batch);
-    if (ret != 0) {
-        LLAMA_LOG_ERROR("%s: failed to decode, ret = %d\n", __func__, ret);
-    }
-
-    return ret;
-}
-
 //
 // chat templates
 //