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Add some comments for python api (#327)

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* Add some comments for python api

* Update setup.py

* Update runtime.py
This commit is contained in:
Jason
2022-10-09 10:05:18 +08:00
committed by GitHub
parent a3fa5989d2
commit 5d4372955f
11 changed files with 239 additions and 13 deletions
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4
.new_docs/api.md Normal file
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@@ -0,0 +1,4 @@
# API说明
- [Python API](./python_apis/index.rst)
- [C++ API](https://paddlepaddle.github.io/FastDeploy/)

1
.new_docs/index.rst
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@@ -14,3 +14,4 @@ FastDeploy
build_and_install/index
quick_start/index
api.md

9
.new_docs/python_apis/image_classification.md Normal file
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@@ -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:
```

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.new_docs/python_apis/index.rst Normal file
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@@ -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

2
.new_docs/references/api_reference.md → .new_docs/python_apis/object_detection.md
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@@ -1,4 +1,4 @@
# Object Detection API Reference
# 目标检测模型部署
## fastdeploy.vision.detection.PPYOLOE

19
.new_docs/python_apis/runtime.md Normal file
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@@ -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:
```

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

0
fastdeploy/libs/__init__.py
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97
python/fastdeploy/runtime.py
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@@ -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):
return self._option.set_paddle_mkldnn(pd_mkldnn)
def set_paddle_mkldnn(self, use_mkldnn=True):
"""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,
getattr(self._option, attr))
message += " {} : {}\t\n".format(attr, getattr(self._option, attr))
message.strip("\n")
message += ")"
return message

22
python/fastdeploy/vision/classification/ppcls/__init__.py
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@@ -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):
return self._model.predict(input_image, topk)
def predict(self, im, topk=1):
"""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)

83
python/fastdeploy/vision/detection/ppdet/__init__.py
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@@ -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):
assert input_image is not None, "The input image data is None."
return self._model.predict(input_image)
def predict(self, im):
"""Detect an 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."