[LLM] First commit the llm deployment code

fastdeploy/platforms/base.py

@@ -0,0 +1,87 @@
+# 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.
+"""
+platform interface file
+"""
+
+import paddle
+import enum
+class _Backend(enum.Enum):
+    NATIVE_ATTN = enum.auto()
+    APPEND_ATTN = enum.auto()
+
+
+class Platform:
+    """
+    Platform base class, all device class will be derived from it
+    """
+    device_name: str
+
+    def is_cuda(self) -> bool:
+        """
+        whether platform is cuda
+        """
+        return paddle.is_compiled_with_cuda()
+
+    def is_npu(self) -> bool:
+        """
+        whether platform is npu
+        """
+        return paddle.is_compiled_with_custom_device("npu")
+
+    def is_xpu(self) -> bool:
+        """
+        whether platform is xpu
+        """
+        return paddle.is_compiled_with_xpu()
+
+    def is_cpu(self) -> bool:
+        """
+        whether platform is cpu
+        """
+        return paddle.device.get_device().lower() == "cpu"
+
+    def is_dcu(self) -> bool:
+        """
+        whether platform is dcu
+        """
+        return paddle.is_compiled_with_rocm()
+
+    @classmethod
+    def get_attention_backend_cls(self, selected_backend):
+        """Get the attention backend"""
+        return ""
+
+    @classmethod
+    def verify_quant(self, quant):
+        """
+        Verify whether the quantization is supported by the current platform.
+        """
+        if self.supported_quantization and quant not in self.supported_quantization:
+            raise ValueError(
+                f"{quant} quantization is currently not supported in "
+                f"{self.device_name}."
+            )
+
+    @classmethod
+    def available(self):
+        """Return whether the device is available"""
+        return True
+
+    @classmethod
+    def supports_fp8(self) -> bool:
+        """
+        Returns whether the current platform supports FP8 types.
+        """
+        return False