Add some comments for python api (#327)

* Add some comments for python api

* Update setup.py

* Update runtime.py

.new_docs/api.md

@@ -0,0 +1,4 @@
+# API说明
+
+- [Python API](./python_apis/index.rst)
+- [C++ API](https://paddlepaddle.github.io/FastDeploy/)

.new_docs/index.rst

@@ -14,3 +14,4 @@ FastDeploy
 
     build_and_install/index
     quick_start/index
+    api.md

.new_docs/python_apis/image_classification.md

@@ -0,0 +1,9 @@
+# 图像分类模型部署
+
+## fastdeploy.vision.classification.PaddleClasModel
+
+```{eval-rst}
+.. autoclass:: fastdeploy.vision.classification.PaddleClasModel
+    :members:
+    :inherited-members:
+```

.new_docs/python_apis/index.rst

@@ -0,0 +1,13 @@
+Python API
+=======================================
+
+FastDeploy支持通过Python编程语言进行部署
+
+..  toctree::
+    :caption: Python API
+    :maxdepth: 3
+    :titlesonly:
+    
+    image_classification.md
+    object_detection.md
+    runtime.md

.new_docs/python_apis/object_detection.md

@@ -1,4 +1,4 @@
-# Object Detection API Reference
+# 目标检测模型部署
 
 ## fastdeploy.vision.detection.PPYOLOE
 

.new_docs/python_apis/runtime.md

@@ -0,0 +1,19 @@
+# Runtime模块使用
+
+FastDeploy Runtime模块可单独使用，通过同样的代码，可快速完成Paddle/ONNX模型在不同硬件，后端上的推理加速部署。
+
+## fastdeploy.RuntimeOption
+
+```{eval-rst}
+.. autoclass:: fastdeploy.RuntimeOption
+    :members:
+    :inherited-members:
+```
+
+## fastdeploy.Runtime
+
+```{eval-rst}
+.. autoclass:: fastdeploy.Runtime
+    :members:
+    :inherited-members:
+```

VERSION_NUMBER

@@ -1 +1 @@
-0.2.1
+0.3.0rc

python/fastdeploy/runtime.py

@@ -13,27 +13,50 @@
 # limitations under the License.
 from __future__ import absolute_import
 import logging
+from . import ModelFormat
 from . import c_lib_wrap as C
 
 
 class Runtime:
+    """FastDeploy Runtime object.
+    """
+
     def __init__(self, runtime_option):
+        """Initialize a FastDeploy Runtime object.
+
+        :param runtime_option: (fastdeploy.RuntimeOption)Options for FastDeploy Runtime
+        """
+
         self._runtime = C.Runtime()
         assert self._runtime.init(
             runtime_option._option), "Initialize Runtime Failed!"
 
     def infer(self, data):
+        """Inference with input data.
+
+        :param data: (dict[str : numpy.ndarray])The input data dict, key value must keep same with the loaded model
+        :return list of numpy.ndarray
+        """
         assert isinstance(data, dict) or isinstance(
             data, list), "The input data should be type of dict or list."
         return self._runtime.infer(data)
 
     def num_inputs(self):
+        """Get number of inputs of the loaded model.
+        """
         return self._runtime.num_inputs()
 
     def num_outputs(self):
+        """Get number of outputs of the loaded model.
+        """
         return self._runtime.num_outputs()
 
     def get_input_info(self, index):
+        """Get input information of the loaded model.
+
+        :param index: (int)Index of the input
+        :return fastdeploy.TensorInfo
+        """
         assert isinstance(
             index, int), "The input parameter index should be type of int."
         assert index < self.num_inputs(
@@ -42,6 +65,11 @@ class Runtime:
         return self._runtime.get_input_info(index)
 
     def get_output_info(self, index):
+        """Get output information of the loaded model.
+
+        :param index: (int)Index of the output
+        :return fastdeploy.TensorInfo
+        """
         assert isinstance(
             index, int), "The input parameter index should be type of int."
         assert index < self.num_outputs(
@@ -51,59 +79,102 @@ class Runtime:
 
 
 class RuntimeOption:
+    """Options for FastDeploy Runtime.
+    """
+
     def __init__(self):
         self._option = C.RuntimeOption()
 
     def set_model_path(self,
                        model_path,
                        params_path="",
-                       model_format=C.ModelFormat.PADDLE):
+                       model_format=ModelFormat.PADDLE):
+        """Set path of model file and parameters file
+
+        :param model_path: (str)Path of model file
+        :param params_path: (str)Path of parameters file
+        :param model_format: (ModelFormat)Format of model, support ModelFormat.PADDLE/ModelFormat.ONNX
+        """
         return self._option.set_model_path(model_path, params_path,
                                            model_format)
 
     def use_gpu(self, device_id=0):
+        """Inference with Nvidia GPU
+
+        :param device_id: (int)The index of GPU will be used for inference, default 0
+        """
         return self._option.use_gpu(device_id)
 
     def use_cpu(self):
+        """Inference with CPU
+        """
         return self._option.use_cpu()
 
     def set_cpu_thread_num(self, thread_num=-1):
+        """Set number of threads if inference with CPU
+
+        :param thread_num: (int)Number of threads, if not positive, means the number of threads is decided by the backend, default -1
+        """
         return self._option.set_cpu_thread_num(thread_num)
 
     def use_paddle_backend(self):
+        """Use Paddle Inference backend, support inference Paddle model on CPU/Nvidia GPU.
+        """
         return self._option.use_paddle_backend()
 
     def use_ort_backend(self):
+        """Use ONNX Runtime backend, support inference Paddle/ONNX model on CPU/Nvidia GPU.
+        """
         return self._option.use_ort_backend()
 
     def use_trt_backend(self):
+        """Use TensorRT backend, support inference Paddle/ONNX model on Nvidia GPU.
+        """
         return self._option.use_trt_backend()
 
     def use_openvino_backend(self):
+        """Use OpenVINO backend, support inference Paddle/ONNX model on CPU.
+        """
         return self._option.use_openvino_backend()
 
     def use_lite_backend(self):
+        """Use Paddle Lite backend, support inference Paddle model on ARM CPU.
+        """
         return self._option.use_lite_backend()
 
-    def set_paddle_mkldnn(self, pd_mkldnn=True):
+    def set_paddle_mkldnn(self, use_mkldnn=True):
-        return self._option.set_paddle_mkldnn(pd_mkldnn)
+        """Enable/Disable MKLDNN while using Paddle Inference backend, mkldnn is enabled by default.
+        """
+        return self._option.set_paddle_mkldnn(use_mkldnn)
 
     def enable_paddle_log_info(self):
+        """Enable print out the debug log information while using Paddle Inference backend, the log information is disabled by default.
+        """
         return self._option.enable_paddle_log_info()
 
     def disable_paddle_log_info(self):
+        """Disable print out the debug log information while using Paddle Inference backend, the log information is disabled by default.
+        """
         return self._option.disable_paddle_log_info()
 
     def set_paddle_mkldnn_cache_size(self, cache_size):
+        """Set size of shape cache while using Paddle Inference backend with MKLDNN enabled, default will cache all the dynamic shape.
+        """
         return self._option.set_paddle_mkldnn_cache_size(cache_size)
 
     def enable_lite_fp16(self):
+        """Enable half precision inference while using Paddle Lite backend on ARM CPU, fp16 is disabled by default.
+        """
         return self._option.enable_lite_fp16()
 
     def disable_lite_fp16(self):
+        """Disable half precision inference while using Paddle Lite backend on ARM CPU, fp16 is disabled by default.
+        """
         return self._option.disable_lite_fp16()
 
     def set_lite_power_mode(self, mode):
+        """Set POWER mode while using Paddle Lite backend on ARM CPU.
+        """
         return self._option.set_lite_power_mode(mode)
 
     def set_trt_input_shape(self,
@@ -111,6 +182,13 @@ class RuntimeOption:
                             min_shape,
                             opt_shape=None,
                             max_shape=None):
+        """Set shape range information while using TensorRT backend with loadding a model contains dynamic input shape. While inference with a new input shape out of the set shape range, the tensorrt engine will be rebuilt to expand the shape range information.
+
+        :param tensor_name: (str)Name of input which has dynamic shape
+        :param min_shape: (list of int)Minimum shape of the input, e.g [1, 3, 224, 224]
+        :param opt_shape: (list of int)Optimize shape of the input, this offten set as the most common input shape, if set to None, it will keep same with min_shape
+        :param max_shape: (list of int)Maximum shape of the input, e.g [8, 3, 224, 224], if set to None, it will keep same with the min_shape
+        """
         if opt_shape is None and max_shape is None:
             opt_shape = min_shape
             max_shape = min_shape
@@ -120,15 +198,25 @@ class RuntimeOption:
                                                 opt_shape, max_shape)
 
     def set_trt_cache_file(self, cache_file_path):
+        """Set a cache file path while using TensorRT backend. While loading a Paddle/ONNX model with set_trt_cache_file("./tensorrt_cache/model.trt"), if file `./tensorrt_cache/model.trt` exists, it will skip building tensorrt engine and load the cache file directly; if file `./tensorrt_cache/model.trt` doesn't exist, it will building tensorrt engine and save the engine as binary string to the cache file.
+
+        :param cache_file_path: (str)Path of tensorrt cache file
+        """
         return self._option.set_trt_cache_file(cache_file_path)
 
     def enable_trt_fp16(self):
+        """Enable half precision inference while using TensorRT backend, notice that not all the Nvidia GPU support FP16, in those cases, will fallback to FP32 inference.
+        """
         return self._option.enable_trt_fp16()
 
     def disable_trt_fp16(self):
+        """Disable half precision inference while suing TensorRT backend.
+        """
         return self._option.disable_trt_fp16()
 
     def set_trt_max_workspace_size(self, trt_max_workspace_size):
+        """Set max workspace size while using TensorRT backend.
+        """
         return self._option.set_trt_max_workspace_size(trt_max_workspace_size)
 
     def __repr__(self):
@@ -139,8 +227,7 @@ class RuntimeOption:
                 continue
             if hasattr(getattr(self._option, attr), "__call__"):
                 continue
-            message += "  {} : {}\t\n".format(attr,
+            message += "  {} : {}\t\n".format(attr, getattr(self._option, attr))
-                                              getattr(self._option, attr))
         message.strip("\n")
         message += ")"
         return message

python/fastdeploy/vision/classification/ppcls/__init__.py

@@ -25,13 +25,29 @@ class PaddleClasModel(FastDeployModel):
                  config_file,
                  runtime_option=None,
                  model_format=ModelFormat.PADDLE):
+        """Load a image classification model exported by PaddleClas.
+
+        :param model_file: (str)Path of model file, e.g resnet50/inference.pdmodel
+        :param params_file: (str)Path of parameters file, e.g resnet50/inference.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param config_file: (str) Path of configuration file for deploy, e.g resnet50/inference_cls.yaml
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
+
         super(PaddleClasModel, self).__init__(runtime_option)
 
-        assert model_format == ModelFormat.PADDLE, "PaddleClasModel only support model format of ModelFormat.Paddle now."
+        assert model_format == ModelFormat.PADDLE, "PaddleClasModel only support model format of ModelFormat.PADDLE now."
         self._model = C.vision.classification.PaddleClasModel(
             model_file, params_file, config_file, self._runtime_option,
             model_format)
         assert self.initialized, "PaddleClas model initialize failed."
 
-    def predict(self, input_image, topk=1):
+    def predict(self, im, topk=1):
-        return self._model.predict(input_image, topk)
+        """Classify an input image
+
+        :param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+        :param topk: (int)The topk result by the classify confidence score, default 1
+        :return: ClassifyResult
+        """
+
+        return self._model.predict(im, topk)

python/fastdeploy/vision/detection/ppdet/__init__.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 from __future__ import absolute_import
+from typing import Union, List
 import logging
 from .... import FastDeployModel, ModelFormat
 from .... import c_lib_wrap as C
@@ -25,6 +26,14 @@ class PPYOLOE(FastDeployModel):
                  config_file,
                  runtime_option=None,
                  model_format=ModelFormat.PADDLE):
+        """Load a PPYOLOE model exported by PaddleDetection.
+
+        :param model_file: (str)Path of model file, e.g ppyoloe/model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g ppyoloe/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
         super(PPYOLOE, self).__init__(runtime_option)
 
         assert model_format == ModelFormat.PADDLE, "PPYOLOE model only support model format of ModelFormat.Paddle now."
@@ -33,9 +42,15 @@ class PPYOLOE(FastDeployModel):
             model_format)
         assert self.initialized, "PPYOLOE model initialize failed."
 
-    def predict(self, input_image):
+    def predict(self, im):
-        assert input_image is not None, "The input image data is None."
+        """Detect an input image
-        return self._model.predict(input_image)
+
+        :param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
+        :return: DetectionResult
+        """
+
+        assert im is not None, "The input image data is None."
+        return self._model.predict(im)
 
 
 class PPYOLO(PPYOLOE):
@@ -45,6 +60,14 @@ class PPYOLO(PPYOLOE):
                  config_file,
                  runtime_option=None,
                  model_format=ModelFormat.PADDLE):
+        """Load a PPYOLO model exported by PaddleDetection.
+
+        :param model_file: (str)Path of model file, e.g ppyolo/model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g ppyolo/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
+
         super(PPYOLOE, self).__init__(runtime_option)
 
         assert model_format == ModelFormat.PADDLE, "PPYOLO model only support model format of ModelFormat.Paddle now."
@@ -61,6 +84,15 @@ class PPYOLOv2(PPYOLOE):
                  config_file,
                  runtime_option=None,
                  model_format=ModelFormat.PADDLE):
+        """Load a PPYOLOv2 model exported by PaddleDetection.
+
+        :param model_file: (str)Path of model file, e.g ppyolov2/model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g ppyolov2/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
+
         super(PPYOLOE, self).__init__(runtime_option)
 
         assert model_format == ModelFormat.PADDLE, "PPYOLOv2 model only support model format of ModelFormat.Paddle now."
@@ -77,6 +109,15 @@ class PaddleYOLOX(PPYOLOE):
                  config_file,
                  runtime_option=None,
                  model_format=ModelFormat.PADDLE):
+        """Load a YOLOX model exported by PaddleDetection.
+
+        :param model_file: (str)Path of model file, e.g yolox/model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g yolox/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
+
         super(PPYOLOE, self).__init__(runtime_option)
 
         assert model_format == ModelFormat.PADDLE, "PaddleYOLOX model only support model format of ModelFormat.Paddle now."
@@ -93,6 +134,15 @@ class PicoDet(PPYOLOE):
                  config_file,
                  runtime_option=None,
                  model_format=ModelFormat.PADDLE):
+        """Load a PicoDet model exported by PaddleDetection.
+
+        :param model_file: (str)Path of model file, e.g picodet/model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g picodet/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
+
         super(PPYOLOE, self).__init__(runtime_option)
 
         assert model_format == ModelFormat.PADDLE, "PicoDet model only support model format of ModelFormat.Paddle now."
@@ -109,6 +159,15 @@ class FasterRCNN(PPYOLOE):
                  config_file,
                  runtime_option=None,
                  model_format=ModelFormat.PADDLE):
+        """Load a FasterRCNN model exported by PaddleDetection.
+
+        :param model_file: (str)Path of model file, e.g fasterrcnn/model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g fasterrcnn/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
+
         super(PPYOLOE, self).__init__(runtime_option)
 
         assert model_format == ModelFormat.PADDLE, "FasterRCNN model only support model format of ModelFormat.Paddle now."
@@ -125,6 +184,15 @@ class YOLOv3(PPYOLOE):
                  config_file,
                  runtime_option=None,
                  model_format=ModelFormat.PADDLE):
+        """Load a YOLOv3 model exported by PaddleDetection.
+
+        :param model_file: (str)Path of model file, e.g yolov3/model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g yolov3/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
+
         super(PPYOLOE, self).__init__(runtime_option)
 
         assert model_format == ModelFormat.PADDLE, "YOLOv3 model only support model format of ModelFormat.Paddle now."
@@ -141,6 +209,15 @@ class MaskRCNN(FastDeployModel):
                  config_file,
                  runtime_option=None,
                  model_format=ModelFormat.PADDLE):
+        """Load a MaskRCNN model exported by PaddleDetection.
+
+        :param model_file: (str)Path of model file, e.g maskrcnn/model.pdmodel
+        :param params_file: (str)Path of parameters file, e.g maskrcnn/model.pdiparams, if the model_fomat is ModelFormat.ONNX, this param will be ignored, can be set as empty string
+        :param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
+        :param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
+        :param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
+        """
+
         super(MaskRCNN, self).__init__(runtime_option)
 
         assert model_format == ModelFormat.PADDLE, "MaskRCNN model only support model format of ModelFormat.Paddle now."