【PIR API adaptor No.127】llm_int8_linear (#58882)

* Update quantized_linear.py

* Update test_llm_int8_linear.py

* Update quantized_linear.py

* Update test_llm_int8_linear.py

Author: Liyulingyue

python/paddle/nn/quant/quantized_linear.py

@@ -15,7 +15,11 @@
 from paddle import _C_ops
 from paddle.base.data_feeder import check_dtype
 from paddle.base.framework import convert_np_dtype_to_dtype_
-from paddle.framework import LayerHelper, in_dynamic_mode
+from paddle.framework import (
+    LayerHelper,
+    in_dynamic_mode,
+    in_dynamic_or_pir_mode,
+)
 
 
 def weight_quantize(x, algo="weight_only_int8"):
@@ -217,7 +221,7 @@ def llm_int8_linear(
             ...    print(out.shape)
             [1, 2, 32]
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         out = _C_ops.llm_int8_linear(x, weight, bias, weight_scale, threshold)
         return out
     else:

test/quantization/test_llm_int8_linear.py

@@ -23,6 +23,7 @@
 from paddle.base import core
 from paddle.base.framework import default_main_program
 from paddle.framework import set_default_dtype
+from paddle.pir_utils import test_with_pir_api
 
 np.random.seed(123)
 paddle.seed(123)
@@ -86,11 +87,12 @@ def get_llm_int8_linear_out(self):
         )
         return out.numpy()
 
+    @test_with_pir_api
     def get_llm_int8_linear_out_static(self):
         paddle.enable_static()
-        main = base.Program()
-        start = base.Program()
-        with base.program_guard(main, start):
+        main = base.static.Program()
+        start = base.static.Program()
+        with base.static.program_guard(main, start):
             x = paddle.static.data("x", self.x.shape, dtype=self.x.dtype)
 
             weight = paddle.static.data(