Fix runtime with python (#63)

fastdeploy/runtime.py

@@ -0,0 +1,121 @@
+# Copyright (c) 2022 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.
+from __future__ import absolute_import
+import logging
+from . import fastdeploy_main as C
+
+
+class Runtime:
+    def __init__(self, runtime_option):
+        self._runtime = C.Runtime()
+        assert self._runtime.init(runtime_option), "Initialize Runtime Failed!"
+
+    def infer(self, data):
+        assert isinstance(data, dict), "The input data should be type of dict."
+        return self._runtime.infer(data)
+
+    def num_inputs(self):
+        return self._runtime.num_inputs()
+
+    def num_outputs(self):
+        return self._runtime.num_outputs()
+
+    def get_input_info(self, index):
+        assert isinstance(
+            index, int), "The input parameter index should be type of int."
+        assert index < self.num_inputs(
+        ), "The input parameter index:{} should less than number of inputs:{}.".format(
+            index, self.num_inputs)
+        return self._runtime.get_input_info(index)
+
+    def get_output_info(self, index):
+        assert isinstance(
+            index, int), "The input parameter index should be type of int."
+        assert index < self.num_outputs(
+        ), "The input parameter index:{} should less than number of outputs:{}.".format(
+            index, self.num_outputs)
+        return self._runtime.get_output_info(index)
+
+
+class RuntimeOption:
+    def __init__(self):
+        self._option = C.RuntimeOption()
+
+    def set_model_path(self, model_path, params_path="",
+                       model_format="paddle"):
+        return self._option.set_model_path(model_path, params_path,
+                                           model_format)
+
+    def use_gpu(self, device_id=0):
+        return self._option.use_gpu(device_id)
+
+    def use_cpu(self):
+        return self._option.use_cpu()
+
+    def set_cpu_thread_num(self, thread_num=8):
+        return self._option.set_cpu_thread_num(thread_num)
+
+    def use_paddle_backend(self):
+        return self._option.use_paddle_backend()
+
+    def use_ort_backend(self):
+        return self._option.use_ort_backend()
+
+    def use_trt_backend(self):
+        return self._option.use_trt_backend()
+
+    def enable_paddle_mkldnn(self):
+        return self._option.enable_paddle_mkldnn()
+
+    def disable_paddle_mkldnn(self):
+        return self._option.disable_paddle_mkldnn()
+
+    def set_paddle_mkldnn_cache_size(self, cache_size):
+        return self._option.set_paddle_mkldnn_cache_size(cache_size)
+
+    def set_trt_input_shape(self,
+                            tensor_name,
+                            min_shape,
+                            opt_shape=None,
+                            max_shape=None):
+        if opt_shape is None and max_shape is None:
+            opt_shape = min_shape
+            max_shape = min_shape
+        else:
+            assert opt_shape is not None and max_shape is not None, "Set min_shape only, or set min_shape, opt_shape, max_shape both."
+        return self._option.set_trt_input_shape(tensor_name, min_shape,
+                                                opt_shape, max_shape)
+
+    def set_trt_cache_file(self, cache_file_path):
+        return self._option.set_trt_cache_file(cache_file_path)
+
+    def enable_trt_fp16(self):
+        return self._option.enable_trt_fp16()
+
+    def disable_trt_fp16(self):
+        return self._option.disable_trt_fp16()
+
+    def __repr__(self):
+        attrs = dir(self._option)
+        message = "RuntimeOption(\n"
+        for attr in attrs:
+            if attr.startswith("__"):
+                continue
+            if hasattr(getattr(self._option, attr), "__call__"):
+                continue
+            message += "  {} : {}\t\n".format(attr,
+                                              getattr(self._option, attr))
+        message.strip("\n")
+        message += ")"
+        return message