fix dynamic to static when export LLM inference model (#56390)

paddle/phi/infermeta/multiary.cc

@@ -1446,7 +1446,8 @@ void FusedBiasActInferMeta(const MetaTensor& x,
                            int quant_round_type,
                            float quant_max_bound,
                            float quant_min_bound,
-                           MetaTensor* out) {
+                           MetaTensor* out,
+                           MetaConfig config) {
   auto x_dims = x.dims();
   PADDLE_ENFORCE_EQ(x_dims.size(),
                     2,
@@ -1455,15 +1456,17 @@ void FusedBiasActInferMeta(const MetaTensor& x,
   auto token_num = x_dims[0];
   auto dim = x_dims[1];
 
-  PADDLE_ENFORCE_GT(
-      x_dims[0],
-      0,
-      phi::errors::InvalidArgument("The size of Attr(rows) must > 0"));
+  if (!config.is_runtime) {
+    PADDLE_ENFORCE_GT(
+        x_dims[0],
+        0,
+        phi::errors::InvalidArgument("The size of Attr(rows) must > 0"));
 
-  PADDLE_ENFORCE_GT(
-      x_dims[1],
-      0,
-      phi::errors::InvalidArgument("The size of Attr(cols) must > 0"));
+    PADDLE_ENFORCE_GT(
+        x_dims[1],
+        0,
+        phi::errors::InvalidArgument("The size of Attr(cols) must > 0"));
+  }
 
   if (act_method == "geglu" || act_method == "swiglu") {
     PADDLE_ENFORCE_EQ(

paddle/phi/infermeta/multiary.h

@@ -318,7 +318,8 @@ void FusedBiasActInferMeta(const MetaTensor& x,
                            int quant_round_type,
                            float quant_max_bound,
                            float quant_min_bound,
-                           MetaTensor* out);
+                           MetaTensor* out,
+                           MetaConfig config = MetaConfig());
 
 void FusedLayerNormInferMeta(const MetaTensor& x,
                              const MetaTensor& bias,

python/paddle/distributed/communication/stream/all_reduce.py

@@ -47,6 +47,7 @@ def _all_reduce_in_static_mode(tensor, op, group, sync_op, use_calc_stream):
             'int8',
             'uint8',
             'bool',
+            'uint16',
         ],
         'all_reduce',
     )

python/paddle/distributed/fleet/layers/mpu/mp_ops.py

@@ -109,7 +109,7 @@ def _c_identity(tensor, group=None):
         check_variable_and_dtype(
             tensor,
             'tensor',
-            ['float16', 'float32', 'float64', 'int32', 'int64'],
+            ['float16', 'float32', 'float64', 'int32', 'int64', 'uint16'],
             '_c_identity',
         )
 
@@ -169,7 +169,7 @@ def _c_concat(tensor, group=None):
         check_variable_and_dtype(
             tensor,
             'tensor',
-            ['float16', 'float32', 'float64', 'int32', 'int64'],
+            ['float16', 'float32', 'float64', 'int32', 'int64', 'uint16'],
             '_c_concat',
         )
 
@@ -235,7 +235,7 @@ def _c_split(tensor, group=None):
         check_variable_and_dtype(
             tensor,
             'tensor',
-            ['float16', 'float32', 'float64', 'int32', 'int64'],
+            ['float16', 'float32', 'float64', 'int32', 'int64', 'uint16'],
             '_c_split',
         )
 
@@ -322,7 +322,7 @@ def _mp_allreduce(
         check_variable_and_dtype(
             tensor,
             'tensor',
-            ['float16', 'float32', 'float64', 'int32', 'int64'],
+            ['float16', 'float32', 'float64', 'int32', 'int64' 'uint16'],
             op_type,
         )
 

python/paddle/incubate/nn/functional/fused_layer_norm.py

@@ -102,7 +102,11 @@ def fused_layer_norm(
     residual_out = helper.create_variable_for_type_inference(dtype=x.dtype)
     outputs_dict['residual_out'] = residual_out
 
-    inputs = {'x': x, 'norm_weight': norm_weight, 'norm_bias': norm_bias}
+    inputs = {'x': x}
+    if norm_weight is not None:
+        inputs['norm_weight'] = norm_weight
+    if norm_bias is not None:
+        inputs['norm_bias'] = norm_bias
     if residual is not None:
         inputs['residual'] = residual
     if bias is not None: