mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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Add some comments for python api (#327)
* Add some comments for python api * Update setup.py * Update runtime.py
This commit is contained in:
Jason
@@ -13,27 +13,50 @@
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# limitations under the License.
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from __future__ import absolute_import
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import logging
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from . import ModelFormat
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from . import c_lib_wrap as C
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class Runtime:
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"""FastDeploy Runtime object.
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"""
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def __init__(self, runtime_option):
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"""Initialize a FastDeploy Runtime object.
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:param runtime_option: (fastdeploy.RuntimeOption)Options for FastDeploy Runtime
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"""
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self._runtime = C.Runtime()
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assert self._runtime.init(
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runtime_option._option), "Initialize Runtime Failed!"
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def infer(self, data):
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"""Inference with input data.
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:param data: (dict[str : numpy.ndarray])The input data dict, key value must keep same with the loaded model
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:return list of numpy.ndarray
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"""
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assert isinstance(data, dict) or isinstance(
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data, list), "The input data should be type of dict or list."
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return self._runtime.infer(data)
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def num_inputs(self):
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"""Get number of inputs of the loaded model.
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"""
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return self._runtime.num_inputs()
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def num_outputs(self):
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"""Get number of outputs of the loaded model.
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"""
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return self._runtime.num_outputs()
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def get_input_info(self, index):
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"""Get input information of the loaded model.
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:param index: (int)Index of the input
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:return fastdeploy.TensorInfo
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"""
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assert isinstance(
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index, int), "The input parameter index should be type of int."
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assert index < self.num_inputs(
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@@ -42,6 +65,11 @@ class Runtime:
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return self._runtime.get_input_info(index)
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def get_output_info(self, index):
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"""Get output information of the loaded model.
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:param index: (int)Index of the output
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:return fastdeploy.TensorInfo
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"""
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assert isinstance(
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index, int), "The input parameter index should be type of int."
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assert index < self.num_outputs(
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@@ -51,59 +79,102 @@ class Runtime:
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class RuntimeOption:
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"""Options for FastDeploy Runtime.
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"""
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def __init__(self):
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self._option = C.RuntimeOption()
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def set_model_path(self,
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model_path,
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params_path="",
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model_format=C.ModelFormat.PADDLE):
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model_format=ModelFormat.PADDLE):
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"""Set path of model file and parameters file
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:param model_path: (str)Path of model file
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:param params_path: (str)Path of parameters file
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:param model_format: (ModelFormat)Format of model, support ModelFormat.PADDLE/ModelFormat.ONNX
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"""
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return self._option.set_model_path(model_path, params_path,
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model_format)
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def use_gpu(self, device_id=0):
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"""Inference with Nvidia GPU
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:param device_id: (int)The index of GPU will be used for inference, default 0
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"""
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return self._option.use_gpu(device_id)
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def use_cpu(self):
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"""Inference with CPU
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"""
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return self._option.use_cpu()
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def set_cpu_thread_num(self, thread_num=-1):
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"""Set number of threads if inference with CPU
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:param thread_num: (int)Number of threads, if not positive, means the number of threads is decided by the backend, default -1
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"""
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return self._option.set_cpu_thread_num(thread_num)
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def use_paddle_backend(self):
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"""Use Paddle Inference backend, support inference Paddle model on CPU/Nvidia GPU.
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"""
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return self._option.use_paddle_backend()
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def use_ort_backend(self):
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"""Use ONNX Runtime backend, support inference Paddle/ONNX model on CPU/Nvidia GPU.
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"""
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return self._option.use_ort_backend()
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def use_trt_backend(self):
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"""Use TensorRT backend, support inference Paddle/ONNX model on Nvidia GPU.
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"""
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return self._option.use_trt_backend()
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def use_openvino_backend(self):
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"""Use OpenVINO backend, support inference Paddle/ONNX model on CPU.
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"""
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return self._option.use_openvino_backend()
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def use_lite_backend(self):
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"""Use Paddle Lite backend, support inference Paddle model on ARM CPU.
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"""
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return self._option.use_lite_backend()
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def set_paddle_mkldnn(self, pd_mkldnn=True):
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return self._option.set_paddle_mkldnn(pd_mkldnn)
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def set_paddle_mkldnn(self, use_mkldnn=True):
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"""Enable/Disable MKLDNN while using Paddle Inference backend, mkldnn is enabled by default.
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"""
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return self._option.set_paddle_mkldnn(use_mkldnn)
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def enable_paddle_log_info(self):
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"""Enable print out the debug log information while using Paddle Inference backend, the log information is disabled by default.
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"""
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return self._option.enable_paddle_log_info()
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def disable_paddle_log_info(self):
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"""Disable print out the debug log information while using Paddle Inference backend, the log information is disabled by default.
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"""
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return self._option.disable_paddle_log_info()
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def set_paddle_mkldnn_cache_size(self, cache_size):
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"""Set size of shape cache while using Paddle Inference backend with MKLDNN enabled, default will cache all the dynamic shape.
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"""
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return self._option.set_paddle_mkldnn_cache_size(cache_size)
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def enable_lite_fp16(self):
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"""Enable half precision inference while using Paddle Lite backend on ARM CPU, fp16 is disabled by default.
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"""
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return self._option.enable_lite_fp16()
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def disable_lite_fp16(self):
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"""Disable half precision inference while using Paddle Lite backend on ARM CPU, fp16 is disabled by default.
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"""
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return self._option.disable_lite_fp16()
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def set_lite_power_mode(self, mode):
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"""Set POWER mode while using Paddle Lite backend on ARM CPU.
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"""
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return self._option.set_lite_power_mode(mode)
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def set_trt_input_shape(self,
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@@ -111,6 +182,13 @@ class RuntimeOption:
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min_shape,
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opt_shape=None,
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max_shape=None):
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"""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.
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:param tensor_name: (str)Name of input which has dynamic shape
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:param min_shape: (list of int)Minimum shape of the input, e.g [1, 3, 224, 224]
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: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
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: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
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"""
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if opt_shape is None and max_shape is None:
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opt_shape = min_shape
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max_shape = min_shape
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@@ -120,15 +198,25 @@ class RuntimeOption:
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opt_shape, max_shape)
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def set_trt_cache_file(self, cache_file_path):
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"""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.
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:param cache_file_path: (str)Path of tensorrt cache file
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"""
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return self._option.set_trt_cache_file(cache_file_path)
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def enable_trt_fp16(self):
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"""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.
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"""
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return self._option.enable_trt_fp16()
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def disable_trt_fp16(self):
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"""Disable half precision inference while suing TensorRT backend.
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"""
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return self._option.disable_trt_fp16()
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def set_trt_max_workspace_size(self, trt_max_workspace_size):
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"""Set max workspace size while using TensorRT backend.
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"""
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return self._option.set_trt_max_workspace_size(trt_max_workspace_size)
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def __repr__(self):
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@@ -139,8 +227,7 @@ class RuntimeOption:
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continue
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if hasattr(getattr(self._option, attr), "__call__"):
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continue
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message += " {} : {}\t\n".format(attr,
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getattr(self._option, attr))
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message += " {} : {}\t\n".format(attr, getattr(self._option, attr))
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message.strip("\n")
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message += ")"
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return message
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@@ -25,13 +25,29 @@ class PaddleClasModel(FastDeployModel):
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a image classification model exported by PaddleClas.
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:param model_file: (str)Path of model file, e.g resnet50/inference.pdmodel
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: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
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:param config_file: (str) Path of configuration file for deploy, e.g resnet50/inference_cls.yaml
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:param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
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:param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
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"""
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super(PaddleClasModel, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "PaddleClasModel only support model format of ModelFormat.Paddle now."
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assert model_format == ModelFormat.PADDLE, "PaddleClasModel only support model format of ModelFormat.PADDLE now."
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self._model = C.vision.classification.PaddleClasModel(
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model_file, params_file, config_file, self._runtime_option,
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model_format)
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assert self.initialized, "PaddleClas model initialize failed."
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def predict(self, input_image, topk=1):
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return self._model.predict(input_image, topk)
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def predict(self, im, topk=1):
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"""Classify an input image
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:param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
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:param topk: (int)The topk result by the classify confidence score, default 1
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:return: ClassifyResult
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"""
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return self._model.predict(im, topk)
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@@ -13,6 +13,7 @@
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# limitations under the License.
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from __future__ import absolute_import
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from typing import Union, List
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import logging
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from .... import FastDeployModel, ModelFormat
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from .... import c_lib_wrap as C
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@@ -25,6 +26,14 @@ class PPYOLOE(FastDeployModel):
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a PPYOLOE model exported by PaddleDetection.
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:param model_file: (str)Path of model file, e.g ppyoloe/model.pdmodel
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: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
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:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
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:param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
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:param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
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"""
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super(PPYOLOE, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "PPYOLOE model only support model format of ModelFormat.Paddle now."
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@@ -33,9 +42,15 @@ class PPYOLOE(FastDeployModel):
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model_format)
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assert self.initialized, "PPYOLOE model initialize failed."
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def predict(self, input_image):
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assert input_image is not None, "The input image data is None."
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return self._model.predict(input_image)
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def predict(self, im):
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"""Detect an input image
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:param im: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
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:return: DetectionResult
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"""
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assert im is not None, "The input image data is None."
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return self._model.predict(im)
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class PPYOLO(PPYOLOE):
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@@ -45,6 +60,14 @@ class PPYOLO(PPYOLOE):
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a PPYOLO model exported by PaddleDetection.
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:param model_file: (str)Path of model file, e.g ppyolo/model.pdmodel
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: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
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:param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
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:param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
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"""
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super(PPYOLOE, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "PPYOLO model only support model format of ModelFormat.Paddle now."
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@@ -61,6 +84,15 @@ class PPYOLOv2(PPYOLOE):
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a PPYOLOv2 model exported by PaddleDetection.
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:param model_file: (str)Path of model file, e.g ppyolov2/model.pdmodel
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: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
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:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
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:param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
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:param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
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"""
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super(PPYOLOE, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "PPYOLOv2 model only support model format of ModelFormat.Paddle now."
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@@ -77,6 +109,15 @@ class PaddleYOLOX(PPYOLOE):
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a YOLOX model exported by PaddleDetection.
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:param model_file: (str)Path of model file, e.g yolox/model.pdmodel
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: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
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:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
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:param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
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:param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
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"""
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super(PPYOLOE, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "PaddleYOLOX model only support model format of ModelFormat.Paddle now."
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@@ -93,6 +134,15 @@ class PicoDet(PPYOLOE):
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a PicoDet model exported by PaddleDetection.
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:param model_file: (str)Path of model file, e.g picodet/model.pdmodel
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: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
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:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
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:param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
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:param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
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"""
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super(PPYOLOE, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "PicoDet model only support model format of ModelFormat.Paddle now."
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@@ -109,6 +159,15 @@ class FasterRCNN(PPYOLOE):
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a FasterRCNN model exported by PaddleDetection.
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:param model_file: (str)Path of model file, e.g fasterrcnn/model.pdmodel
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: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
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:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
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:param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
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:param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
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"""
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super(PPYOLOE, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "FasterRCNN model only support model format of ModelFormat.Paddle now."
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@@ -125,6 +184,15 @@ class YOLOv3(PPYOLOE):
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a YOLOv3 model exported by PaddleDetection.
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:param model_file: (str)Path of model file, e.g yolov3/model.pdmodel
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: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
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:param config_file: (str)Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
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:param runtime_option: (fastdeploy.RuntimeOption)RuntimeOption for inference this model, if it's None, will use the default backend on CPU
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:param model_format: (fastdeploy.ModelForamt)Model format of the loaded model
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"""
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super(PPYOLOE, self).__init__(runtime_option)
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assert model_format == ModelFormat.PADDLE, "YOLOv3 model only support model format of ModelFormat.Paddle now."
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@@ -141,6 +209,15 @@ class MaskRCNN(FastDeployModel):
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config_file,
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runtime_option=None,
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model_format=ModelFormat.PADDLE):
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"""Load a MaskRCNN model exported by PaddleDetection.
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: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."
|
||||
|
||||
Reference in New Issue
Block a user