Revert "Add support for batching (#241)" (#269)

This reverts commit 4a4a52a.

Author: lantiga

docs/commands.md

@@ -87,22 +87,12 @@ AI.TENSORGET foo BLOB
 Set a model.
 
 ```sql
-AI.MODELSET model_key backend device [BATCHSIZE n [MINBATCHSIZE m]] [INPUTS name1 name2 ... OUTPUTS name1 name2 ...] model_blob
+AI.MODELSET model_key backend device [INPUTS name1 name2 ... OUTPUTS name1 name2 ...] model_blob
 ```
 
 * model_key - Key for storing the model
 * backend - The backend corresponding to the model being set. Allowed values: `TF`, `TORCH`, `ONNX`.
 * device - Device where the model is loaded and where the computation will run. Allowed values: `CPU`, `GPU`.
-* BATCHSIZE n - Batch incoming requests from multiple clients if they hit the same model and if input tensors have the same
-                shape. Upon MODELRUN, the request queue is visited, input tensors from compatible requests are concatenated
-                along the 0-th (batch) dimension, up until BATCHSIZE is exceeded. The model is then run for the entire batch,
-                results are unpacked back among the individual requests and the respective clients are unblocked.
-                If the batch size of the inputs to the first request in the queue exceeds BATCHSIZE, the request is served
-                in any case. Default is 0 (no batching).
-* MINBATCHSIZE m - Do not execute a MODELRUN until the batch size has reached MINBATCHSIZE. This is primarily used to force
-                   batching during testing, but it can also be used under normal operation. In this case, note that requests
-                   for which MINBATCHSIZE is not reached will hang indefinitely.
-                   Default is 0 (no minimum batch size).
 * INPUTS name1 name2 ... - Name of the nodes in the provided graph corresponding to inputs [`TF` backend only]
 * OUTPUTS name1 name2 ... - Name of the nodes in the provided graph corresponding to outputs [`TF` backend only]
 * model_blob - Binary buffer containing the model protobuf saved from a supported backend
@@ -121,14 +111,6 @@ AI.MODELSET resnet18 TF CPU INPUTS in1 OUTPUTS linear4 < foo.pb
 AI.MODELSET mnist_net ONNX CPU < mnist.onnx
 ```
 
-```sql
-AI.MODELSET mnist_net ONNX CPU BATCHSIZE 10 < mnist.onnx
-```
-
-```sql
-AI.MODELSET resnet18 TF CPU BATCHSIZE 10 MINBATCHSIZE 6 INPUTS in1 OUTPUTS linear4 < foo.pb
-```
-
 ## AI.MODELGET
 
 Get a model.

src/backends.c

@@ -74,7 +74,7 @@ int RAI_LoadBackend_TensorFlow(RedisModuleCtx *ctx, const char *path) {
   }
   init_backend(RedisModule_GetApi);
 
-  backend.model_create_with_nodes = (RAI_Model* (*)(RAI_Backend, const char*, RAI_ModelOpts,
+  backend.model_create_with_nodes = (RAI_Model* (*)(RAI_Backend, const char*,
                                      size_t, const char**, size_t, const char**,
                                      const char*, size_t, RAI_Error*))
                                      (unsigned long) dlsym(handle, "RAI_ModelCreateTF");
@@ -140,7 +140,7 @@ int RAI_LoadBackend_TFLite(RedisModuleCtx *ctx, const char *path) {
   }
   init_backend(RedisModule_GetApi);
 
-  backend.model_create = (RAI_Model* (*)(RAI_Backend, const char*, RAI_ModelOpts,
+  backend.model_create = (RAI_Model* (*)(RAI_Backend, const char*,
                           const char*, size_t, RAI_Error*))
                          (unsigned long) dlsym(handle, "RAI_ModelCreateTFLite");
   if (backend.model_create == NULL) {
@@ -205,7 +205,7 @@ int RAI_LoadBackend_Torch(RedisModuleCtx *ctx, const char *path) {
   }
   init_backend(RedisModule_GetApi);
 
-  backend.model_create = (RAI_Model* (*)(RAI_Backend, const char*, RAI_ModelOpts,
+  backend.model_create = (RAI_Model* (*)(RAI_Backend, const char*,
                           const char*, size_t, RAI_Error*))
                          (unsigned long) dlsym(handle, "RAI_ModelCreateTorch");
   if (backend.model_create == NULL) {
@@ -294,7 +294,7 @@ int RAI_LoadBackend_ONNXRuntime(RedisModuleCtx *ctx, const char *path) {
   }
   init_backend(RedisModule_GetApi);
 
-  backend.model_create = (RAI_Model* (*)(RAI_Backend, const char*, RAI_ModelOpts,
+  backend.model_create = (RAI_Model* (*)(RAI_Backend, const char*,
                           const char*, size_t, RAI_Error*))
                          (unsigned long) dlsym(handle, "RAI_ModelCreateORT");
   if (backend.model_create == NULL) {

src/backends.h

@@ -8,10 +8,10 @@
 #include "err.h"
 
 typedef struct RAI_LoadedBackend {
-  RAI_Model* (*model_create_with_nodes)(RAI_Backend, const char*, RAI_ModelOpts,
+  RAI_Model* (*model_create_with_nodes)(RAI_Backend, const char*,
                                         size_t, const char**, size_t, const char**,
                                         const char*, size_t, RAI_Error*);
-  RAI_Model* (*model_create)(RAI_Backend, const char*, RAI_ModelOpts,
+  RAI_Model* (*model_create)(RAI_Backend, const char*,
                              const char*, size_t, RAI_Error*);
   void (*model_free)(RAI_Model*, RAI_Error*);
   int (*model_run)(RAI_ModelRunCtx*, RAI_Error*);