llama : support input embeddings directly (#1910)

* add interface for float input

* fixed inpL shape and type

* add examples of input floats

* add test example for embd input

* fixed sampling

* add free for context

* fixed add end condition for generating

* add examples for llava.py

* add READMD for llava.py

* add READMD for llava.py

* add example of PandaGPT

* refactor the interface and fixed the styles

* add cmake build for embd-input

* add cmake build for embd-input

* Add MiniGPT-4 example

* change the order of the args of llama_eval_internal

* fix ci error

1 files changed, 35 insertions, 0 deletions

diff --git a/examples/embd-input/embd-input-test.cpp b/examples/embd-input/embd-input-test.cpp
new file mode 100644
index 00000000..e5e040f6
--- /dev/null
+++ b/examples/embd-input/embd-input-test.cpp
@@ -0,0 +1,35 @@
+#include "embd-input.h"
+#include <stdlib.h>
+#include <random>
+#include <string.h>
+
+int main(int argc, char** argv) {
+
+    auto mymodel = create_mymodel(argc, argv);
+    int N = 10;
+    int max_tgt_len = 500;
+    int n_embd = llama_n_embd(mymodel->ctx);
+
+    // add random float embd to test evaluation
+    float * data = new float[N*n_embd];
+    std::default_random_engine e;
+    std::uniform_real_distribution<float>  u(0,1);
+    for (int i=0;i<N*n_embd;i++) {
+        data[i] = u(e);
+    }
+
+    eval_string(mymodel, "user: what is the color of the flag of UN?");
+    eval_float(mymodel, data, N);
+    eval_string(mymodel, "assistant:");
+    eval_string(mymodel, mymodel->params.prompt.c_str());
+    const char* tmp;
+    for (int i=0; i<max_tgt_len; i++) {
+        tmp = sampling(mymodel);
+        if (strcmp(tmp, "</s>")==0) break;
+        printf("%s", tmp);
+        fflush(stdout);
+    }
+    printf("\n");
+    free_mymodel(mymodel);
+    return 0;
+}