[LLM] First commit the llm deployment code

fastdeploy/platforms/utils.py

@@ -0,0 +1,46 @@
+"""
+# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+ !! This file will be deleted after the platform is fully functional
+"""
+
+import numpy as np
+import paddle
+
+def convert_to_npu_dequant_scale(deq_scale):
+    """
+    Convert dequantization scale for NPU.
+
+    Args:
+        deq_scale (paddle.Tensor): The original dequantization scale tensor.
+
+    Returns:
+        paddle.Tensor: Converted dequantization scale tensor for NPU.
+        If NPU is not available, the original tensor is returned.
+
+    This function is designed to prepare the dequantization scale tensor for NPU.
+    It first checks if NPU is available. If not, it simply returns the original tensor.
+    If NPU is available, it converts the tensor into a specific format required by NPU
+    by stacking the original scale values with zeros, reshaping, and converting the data
+    type to int64 before returning it as a paddle tensor.
+    """
+    if not paddle.is_compiled_with_custom_device("npu"):
+        return deq_scale
+    arr = deq_scale.numpy()
+    new_deq_scale = np.stack(
+        [arr.reshape(-1, 1),
+         np.zeros_like(arr).reshape(-1, 1)], axis=-1).reshape(-1)
+    return paddle.to_tensor(
+        np.frombuffer(new_deq_scale.tobytes(), dtype=np.int64))