dummy import fd (#5192)

fastdeploy/cache_manager/ops.py

@@ -1,77 +1,107 @@
+"""
+# Copyright (c) 2025  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.
+"""
+
 import paddle
 
 from fastdeploy.platforms import current_platform
 
-if current_platform.is_cuda():
-    from fastdeploy.model_executor.ops.gpu import (
-        cuda_host_alloc,
-        cuda_host_free,
-        get_data_ptr_ipc,
-        get_output_kv_signal,
-        ipc_sent_key_value_cache_by_remote_ptr,
-        ipc_sent_key_value_cache_by_remote_ptr_block_sync,
-        set_data_ipc,
-        share_external_data,
-        swap_cache_all_layers,
-        unset_data_ipc,
-    )
+try:
+    if current_platform.is_cuda():
+        from fastdeploy.model_executor.ops.gpu import (
+            cuda_host_alloc,
+            cuda_host_free,
+            get_data_ptr_ipc,
+            get_output_kv_signal,
+            ipc_sent_key_value_cache_by_remote_ptr,
+            ipc_sent_key_value_cache_by_remote_ptr_block_sync,
+            set_data_ipc,
+            share_external_data,
+            swap_cache_all_layers,
+            unset_data_ipc,
+        )
 
-    memory_allocated = paddle.device.cuda.memory_allocated
+        memory_allocated = paddle.device.cuda.memory_allocated
 
-    def get_peer_mem_addr(*args, **kwargs):
-        raise RuntimeError("CUDA no need of get_peer_mem_addr!")
+        def get_peer_mem_addr(*args, **kwargs):
+            raise RuntimeError("CUDA no need of get_peer_mem_addr!")
 
-elif current_platform.is_xpu():
-    from fastdeploy.model_executor.ops.xpu import (
-        cuda_host_alloc,
-        cuda_host_free,
-        get_output_kv_signal,
-        get_peer_mem_addr,
-        set_data_ipc,
-        share_external_data,
-        swap_cache_all_layers,
-    )
+    elif current_platform.is_xpu():
+        from fastdeploy.model_executor.ops.xpu import (
+            cuda_host_alloc,
+            cuda_host_free,
+            get_output_kv_signal,
+            get_peer_mem_addr,
+            set_data_ipc,
+            share_external_data,
+            swap_cache_all_layers,
+        )
 
+        unset_data_ipc = None
+        memory_allocated = paddle.device.xpu.memory_allocated
+
+        def get_data_ptr_ipc(*args, **kwargs):
+            raise RuntimeError("XPU get_data_ptr_ipc UNIMPLENENTED!")
+
+        def ipc_sent_key_value_cache_by_remote_ptr(*args, **kwargs):
+            raise RuntimeError("XPU ipc_sent_key_value_cache_by_remote_ptr UNIMPLENENTED")
+
+        def ipc_sent_key_value_cache_by_remote_ptr_block_sync(*args, **kwargs):
+            raise RuntimeError("XPU No ipc_sent_key_value_cache_by_remote_ptr UNIMPLENENTED")
+
+    else:
+        raise RuntimeError("Prefix cache ops only supported CUDA nor XPU platform ")
+
+    def set_device(device):
+        if current_platform.is_cuda():
+            paddle.set_device(f"gpu:{device}")
+        elif current_platform.is_xpu():
+            paddle.set_device(f"xpu:{device}")
+        else:
+            raise RuntimeError("No supported platform")
+
+    def share_external_data_(cache, cache_name, cache_shape, use_ipc):
+        if current_platform.is_cuda():
+            cache = share_external_data(cache, cache_name, cache_shape)
+        elif current_platform.is_xpu():
+            cache = share_external_data(cache, cache_name, cache_shape, use_ipc)
+        else:
+            raise RuntimeError("No supported platform")
+        return cache
+
+    def get_all_visible_devices():
+        if current_platform.is_xpu():
+            return "XPU_VISIBLE_DEVICES=0,1,2,3,4,5,6,7"
+        else:
+            return "CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7"
+
+except:
+    cuda_host_alloc = None
+    cuda_host_free = None
+    set_data_ipc = None
+    share_external_data_ = None
+    swap_cache_all_layers = None
     unset_data_ipc = None
-    memory_allocated = paddle.device.xpu.memory_allocated
-
-    def get_data_ptr_ipc(*args, **kwargs):
-        raise RuntimeError("XPU get_data_ptr_ipc UNIMPLENENTED!")
-
-    def ipc_sent_key_value_cache_by_remote_ptr(*args, **kwargs):
-        raise RuntimeError("XPU ipc_sent_key_value_cache_by_remote_ptr UNIMPLENENTED")
-
-    def ipc_sent_key_value_cache_by_remote_ptr_block_sync(*args, **kwargs):
-        raise RuntimeError("XPU No ipc_sent_key_value_cache_by_remote_ptr UNIMPLENENTED")
-
-else:
-    raise RuntimeError("Prefix cache ops only supported CUDA nor XPU platform ")
-
-
-def set_device(device):
-    if current_platform.is_cuda():
-        paddle.set_device(f"gpu:{device}")
-    elif current_platform.is_xpu():
-        paddle.set_device(f"xpu:{device}")
-    else:
-        raise RuntimeError("No supported platform")
-
-
-def share_external_data_(cache, cache_name, cache_shape, use_ipc):
-    if current_platform.is_cuda():
-        cache = share_external_data(cache, cache_name, cache_shape)
-    elif current_platform.is_xpu():
-        cache = share_external_data(cache, cache_name, cache_shape, use_ipc)
-    else:
-        raise RuntimeError("No supported platform")
-    return cache
-
-
-def get_all_visible_devices():
-    if current_platform.is_xpu():
-        return "XPU_VISIBLE_DEVICES=0,1,2,3,4,5,6,7"
-    else:
-        return "CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7"
+    set_device = None
+    memory_allocated = None
+    get_output_kv_signal = None
+    get_data_ptr_ipc = None
+    ipc_sent_key_value_cache_by_remote_ptr = None
+    ipc_sent_key_value_cache_by_remote_ptr_block_sync = None
+    get_peer_mem_addr = None
+    get_all_visible_devices = None
 
 
 __all__ = [