fix: no allow client to change server batch size (#787)

jina-ai · Jul 28, 2022 · 1db43b4 · 1db43b4
1 parent 87928a7
commit 1db43b4
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Showing 3 changed files with 6 additions and 10 deletions.
diff --git a/server/clip_server/executors/clip_onnx.py b/server/clip_server/executors/clip_onnx.py
@@ -105,9 +105,7 @@ async def rank(self, docs: 'DocumentArray', parameters: Dict, **kwargs):
 
     @requests
     async def encode(self, docs: 'DocumentArray', parameters: Dict = {}, **kwargs):
-
         traversal_paths = parameters.get('traversal_paths', self._traversal_paths)
-        minibatch_size = parameters.get('minibatch_size', self._minibatch_size)
 
         _img_da = DocumentArray()
         _txt_da = DocumentArray()
@@ -118,7 +116,7 @@ async def encode(self, docs: 'DocumentArray', parameters: Dict = {}, **kwargs):
         if _img_da:
             for minibatch, batch_data in _img_da.map_batch(
                 self._preproc_images,
-                batch_size=minibatch_size,
+                batch_size=self._minibatch_size,
                 pool=self._pool,
             ):
                 with self.monitor(
@@ -131,7 +129,7 @@ async def encode(self, docs: 'DocumentArray', parameters: Dict = {}, **kwargs):
         if _txt_da:
             for minibatch, batch_data in _txt_da.map_batch(
                 self._preproc_texts,
-                batch_size=minibatch_size,
+                batch_size=self._minibatch_size,
                 pool=self._pool,
             ):
                 with self.monitor(

diff --git a/server/clip_server/executors/clip_tensorrt.py b/server/clip_server/executors/clip_tensorrt.py
@@ -81,7 +81,6 @@ async def rank(self, docs: 'DocumentArray', parameters: Dict, **kwargs):
     @requests
     async def encode(self, docs: 'DocumentArray', parameters: Dict = {}, **kwargs):
         traversal_paths = parameters.get('traversal_paths', self._traversal_paths)
-        minibatch_size = parameters.get('minibatch_size', self._minibatch_size)
 
         _img_da = DocumentArray()
         _txt_da = DocumentArray()
@@ -92,7 +91,7 @@ async def encode(self, docs: 'DocumentArray', parameters: Dict = {}, **kwargs):
         if _img_da:
             for minibatch, batch_data in _img_da.map_batch(
                 self._preproc_images,
-                batch_size=minibatch_size,
+                batch_size=self._minibatch_size,
                 pool=self._pool,
             ):
                 with self.monitor(
@@ -111,7 +110,7 @@ async def encode(self, docs: 'DocumentArray', parameters: Dict = {}, **kwargs):
         if _txt_da:
             for minibatch, batch_data in _txt_da.map_batch(
                 self._preproc_texts,
-                batch_size=minibatch_size,
+                batch_size=self._minibatch_size,
                 pool=self._pool,
             ):
                 with self.monitor(

diff --git a/server/clip_server/executors/clip_torch.py b/server/clip_server/executors/clip_torch.py
@@ -91,7 +91,6 @@ async def rank(self, docs: 'DocumentArray', parameters: Dict, **kwargs):
     @requests
     async def encode(self, docs: 'DocumentArray', parameters: Dict = {}, **kwargs):
         traversal_paths = parameters.get('traversal_paths', self._traversal_paths)
-        minibatch_size = parameters.get('minibatch_size', self._minibatch_size)
 
         _img_da = DocumentArray()
         _txt_da = DocumentArray()
@@ -103,7 +102,7 @@ async def encode(self, docs: 'DocumentArray', parameters: Dict = {}, **kwargs):
             if _img_da:
                 for minibatch, batch_data in _img_da.map_batch(
                     self._preproc_images,
-                    batch_size=minibatch_size,
+                    batch_size=self._minibatch_size,
                     pool=self._pool,
                 ):
                     with self.monitor(
@@ -121,7 +120,7 @@ async def encode(self, docs: 'DocumentArray', parameters: Dict = {}, **kwargs):
             if _txt_da:
                 for minibatch, batch_data in _txt_da.map_batch(
                     self._preproc_texts,
-                    batch_size=minibatch_size,
+                    batch_size=self._minibatch_size,
                     pool=self._pool,
                 ):
                     with self.monitor(