added NA for torch and TFLITE

Author: DvirDukhan

src/backends.c

@@ -224,6 +224,17 @@ int RAI_LoadBackend_TFLite(RedisModuleCtx *ctx, const char *path) {
         return REDISMODULE_ERR;
     }
 
+    backend.get_version =
+        (const char *(*)(void))(unsigned long)dlsym(handle, "RAI_GetBackendVersionTFLite");
+    if (backend.get_version == NULL) {
+        dlclose(handle);
+        RedisModule_Log(ctx, "warning",
+                        "Backend does not export RAI_GetBackendVersionTFLite. TFLite backend "
+                        "not loaded from %s",
+                        path);
+        return REDISMODULE_ERR;
+    }
+
     RAI_backends.tflite = backend;
 
     RedisModule_Log(ctx, "notice", "TFLITE backend loaded from %s", path);
@@ -338,6 +349,17 @@ int RAI_LoadBackend_Torch(RedisModuleCtx *ctx, const char *path) {
         return REDISMODULE_ERR;
     }
 
+    backend.get_version =
+        (const char *(*)(void))(unsigned long)dlsym(handle, "RAI_GetBackendVersionTorch");
+    if (backend.get_version == NULL) {
+        dlclose(handle);
+        RedisModule_Log(ctx, "warning",
+                        "Backend does not export RAI_GetBackendVersionTorch. TORCH backend "
+                        "not loaded from %s",
+                        path);
+        return REDISMODULE_ERR;
+    }
+
     RAI_backends.torch = backend;
 
     RedisModule_Log(ctx, "notice", "TORCH backend loaded from %s", path);

src/backends/tflite.c

@@ -237,3 +237,5 @@ int RAI_ModelSerializeTFLite(RAI_Model *model, char **buffer, size_t *len, RAI_E
 
     return 0;
 }
+
+const char *RAI_GetBackendVersionTFLite(void) { return "NA"; }

src/backends/tflite.h

@@ -1,5 +1,4 @@
-#ifndef SRC_BACKENDS_TFLITE_H_
-#define SRC_BACKENDS_TFLITE_H_
+#pragma once
 
 #include "config.h"
 #include "tensor_struct.h"
@@ -17,4 +16,4 @@ int RAI_ModelRunTFLite(RAI_ModelRunCtx **mctxs, RAI_Error *error);
 
 int RAI_ModelSerializeTFLite(RAI_Model *model, char **buffer, size_t *len, RAI_Error *error);
 
-#endif /* SRC_BACKENDS_TFLITE_H_ */
+const char *RAI_GetBackendVersionTFLite(void);

src/backends/torch.c

@@ -367,3 +367,5 @@ int RAI_ScriptRunTorch(RAI_ScriptRunCtx *sctx, RAI_Error *error) {
 
     return 0;
 }
+
+const char *RAI_GetBackendVersionTorch(void) { return "NA"; }

src/backends/torch.h

@@ -1,5 +1,4 @@
-#ifndef SRC_BACKENDS_TORCH_H_
-#define SRC_BACKENDS_TORCH_H_
+#pragma once
 
 #include "config.h"
 #include "tensor_struct.h"
@@ -24,4 +23,4 @@ void RAI_ScriptFreeTorch(RAI_Script *script, RAI_Error *error);
 
 int RAI_ScriptRunTorch(RAI_ScriptRunCtx *sctx, RAI_Error *error);
 
-#endif /* SRC_BACKENDS_TORCH_H_ */
+const char *RAI_GetBackendVersionTorch(void);

src/redisai.c

@@ -844,6 +844,16 @@ void _RedisAI_Info(RedisModuleCtx *ctx) {
         RedisModule_ReplyWithSimpleString(ctx, RAI_backends.tf.get_version());
     }
 
+    if (RAI_backends.torch.get_version) {
+        RedisModule_ReplyWithSimpleString(ctx, "Torch version");
+        RedisModule_ReplyWithSimpleString(ctx, RAI_backends.torch.get_version());
+    }
+
+    if (RAI_backends.tflite.get_version) {
+        RedisModule_ReplyWithSimpleString(ctx, "TFLite version");
+        RedisModule_ReplyWithSimpleString(ctx, RAI_backends.tflite.get_version());
+    }
+
     if (RAI_backends.onnx.get_version) {
         RedisModule_ReplyWithSimpleString(ctx, "ONNX version");
         RedisModule_ReplyWithSimpleString(ctx, RAI_backends.onnx.get_version());

tests/flow/tests_pytorch.py

@@ -984,3 +984,22 @@ def test_modelget_for_tuple_output(env):
     env.assertEqual(ret[9], 0)
     env.assertEqual(len(ret[11]), 2)
     env.assertEqual(len(ret[13]), 2)
+
+def test_torch_info(env):
+    if not TEST_PT:
+        env.debugPrint("skipping {}".format(sys._getframe().f_code.co_name), force=True)
+        return
+    con = env.getConnection()
+
+    ret = con.execute_command('AI.INFO')
+    env.assertEqual(6, len(ret))
+
+    test_data_path = os.path.join(os.path.dirname(__file__), 'test_data')
+    model_filename = os.path.join(test_data_path, 'pt-minimal-bb.pt')
+    with open(model_filename, 'rb') as f:
+        model_pb = f.read()
+    ret = con.execute_command('AI.MODELSET', 'm{1}', 'TORCH', DEVICE, 'BLOB', model_pb)
+
+    ret = con.execute_command('AI.INFO')
+    env.assertEqual(8, len(ret))
+    env.assertEqual(b'Torch version', ret[6])

tests/flow/tests_tflite.py

@@ -354,3 +354,24 @@ def test_tflite_model_rdb_save_load(env):
     env.assertTrue(model_serialized_memory == model_serialized_after_rdbload)
     # Assert input model binary is equal to loaded model binary
     env.assertTrue(model_pb == model_serialized_after_rdbload)
+
+def test_tflite_info(env):
+    if not TEST_TFLITE:
+        env.debugPrint("skipping {}".format(sys._getframe().f_code.co_name), force=True)
+        return
+    con = env.getConnection()
+
+    ret = con.execute_command('AI.INFO')
+    env.assertEqual(6, len(ret))
+
+    test_data_path = os.path.join(os.path.dirname(__file__), 'test_data')
+    model_filename = os.path.join(test_data_path, 'mnist_model_quant.tflite')
+
+    with open(model_filename, 'rb') as f:
+        model_pb = f.read()
+
+    ret = con.execute_command('AI.MODELSET', 'mnist{1}', 'TFLITE', 'CPU', 'BLOB', model_pb)
+
+    ret = con.execute_command('AI.INFO')
+    env.assertEqual(8, len(ret))
+    env.assertEqual(b'TFLite version', ret[6])