Add PaddlePaddle export and inference (#9240)
* Add PaddlePaddle Model Export Test on Yolov5 DockerEnviroment with paddlepaddle-gpu v2.2 Signed-off-by: Katteria <39751846+kisaragychihaya@users.noreply.github.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Cleanup Paddle Export Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update common.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update export.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update export.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update export.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update export.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Use PyTorch2Paddle Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Paddle no longer requires ONNX Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update export.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update export.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update benchmarks.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add inference code of PaddlePaddle Signed-off-by: Katteria <39751846+kisaragychihaya@users.noreply.github.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update common.py Signed-off-by: Katteria <39751846+kisaragychihaya@users.noreply.github.com> * Update common.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add paddlepaddle-gpu install if cuda Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update common.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update common.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update common.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Signed-off-by: Katteria <39751846+kisaragychihaya@users.noreply.github.com> Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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@@ -15,6 +15,7 @@ TensorFlow GraphDef | `pb` | yolov5s.pb
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TensorFlow Lite | `tflite` | yolov5s.tflite
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TensorFlow Edge TPU | `edgetpu` | yolov5s_edgetpu.tflite
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TensorFlow.js | `tfjs` | yolov5s_web_model/
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PaddlePaddle | `paddle` | yolov5s_paddle_model/
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Requirements:
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$ pip install -r requirements.txt coremltools onnx onnx-simplifier onnxruntime openvino-dev tensorflow-cpu # CPU
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@@ -54,7 +55,6 @@ from pathlib import Path
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import pandas as pd
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import torch
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import yaml
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from torch.utils.mobile_optimizer import optimize_for_mobile
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FILE = Path(__file__).resolve()
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@@ -68,7 +68,7 @@ from models.experimental import attempt_load
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from models.yolo import ClassificationModel, Detect
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from utils.dataloaders import LoadImages
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from utils.general import (LOGGER, Profile, check_dataset, check_img_size, check_requirements, check_version,
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check_yaml, colorstr, file_size, get_default_args, print_args, url2file)
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check_yaml, colorstr, file_size, get_default_args, print_args, url2file, yaml_save)
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from utils.torch_utils import select_device, smart_inference_mode
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@@ -85,7 +85,8 @@ def export_formats():
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['TensorFlow GraphDef', 'pb', '.pb', True, True],
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['TensorFlow Lite', 'tflite', '.tflite', True, False],
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['TensorFlow Edge TPU', 'edgetpu', '_edgetpu.tflite', False, False],
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['TensorFlow.js', 'tfjs', '_web_model', False, False],]
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['TensorFlow.js', 'tfjs', '_web_model', False, False],
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['PaddlePaddle', 'paddle', '_paddle_model', True, True],]
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return pd.DataFrame(x, columns=['Format', 'Argument', 'Suffix', 'CPU', 'GPU'])
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@@ -180,7 +181,7 @@ def export_onnx(model, im, file, opset, train, dynamic, simplify, prefix=colorst
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@try_export
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def export_openvino(model, file, half, prefix=colorstr('OpenVINO:')):
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def export_openvino(file, metadata, half, prefix=colorstr('OpenVINO:')):
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# YOLOv5 OpenVINO export
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check_requirements('openvino-dev') # requires openvino-dev: https://pypi.org/project/openvino-dev/
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import openvino.inference_engine as ie
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@@ -189,9 +190,23 @@ def export_openvino(model, file, half, prefix=colorstr('OpenVINO:')):
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f = str(file).replace('.pt', f'_openvino_model{os.sep}')
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cmd = f"mo --input_model {file.with_suffix('.onnx')} --output_dir {f} --data_type {'FP16' if half else 'FP32'}"
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subprocess.check_output(cmd.split()) # export
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with open(Path(f) / file.with_suffix('.yaml').name, 'w') as g:
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yaml.dump({'stride': int(max(model.stride)), 'names': model.names}, g) # add metadata.yaml
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subprocess.run(cmd.split(), check=True, env=os.environ) # export
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yaml_save(Path(f) / file.with_suffix('.yaml').name, metadata) # add metadata.yaml
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return f, None
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@try_export
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def export_paddle(model, im, file, metadata, prefix=colorstr('PaddlePaddle:')):
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# YOLOv5 Paddle export
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check_requirements(('paddlepaddle', 'x2paddle'))
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import x2paddle
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from x2paddle.convert import pytorch2paddle
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LOGGER.info(f'\n{prefix} starting export with X2Paddle {x2paddle.__version__}...')
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f = str(file).replace('.pt', f'_paddle_model{os.sep}')
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pytorch2paddle(module=model, save_dir=f, jit_type='trace', input_examples=[im]) # export
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yaml_save(Path(f) / file.with_suffix('.yaml').name, metadata) # add metadata.yaml
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return f, None
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@@ -464,7 +479,7 @@ def run(
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fmts = tuple(export_formats()['Argument'][1:]) # --include arguments
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flags = [x in include for x in fmts]
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assert sum(flags) == len(include), f'ERROR: Invalid --include {include}, valid --include arguments are {fmts}'
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jit, onnx, xml, engine, coreml, saved_model, pb, tflite, edgetpu, tfjs = flags # export booleans
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jit, onnx, xml, engine, coreml, saved_model, pb, tflite, edgetpu, tfjs, paddle = flags # export booleans
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file = Path(url2file(weights) if str(weights).startswith(('http:/', 'https:/')) else weights) # PyTorch weights
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# Load PyTorch model
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@@ -497,47 +512,48 @@ def run(
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if half and not coreml:
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im, model = im.half(), model.half() # to FP16
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shape = tuple((y[0] if isinstance(y, tuple) else y).shape) # model output shape
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metadata = {'stride': int(max(model.stride)), 'names': model.names} # model metadata
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LOGGER.info(f"\n{colorstr('PyTorch:')} starting from {file} with output shape {shape} ({file_size(file):.1f} MB)")
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# Exports
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f = [''] * 10 # exported filenames
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f = [''] * len(fmts) # exported filenames
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warnings.filterwarnings(action='ignore', category=torch.jit.TracerWarning) # suppress TracerWarning
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if jit:
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if jit: # TorchScript
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f[0], _ = export_torchscript(model, im, file, optimize)
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if engine: # TensorRT required before ONNX
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f[1], _ = export_engine(model, im, file, half, dynamic, simplify, workspace, verbose)
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if onnx or xml: # OpenVINO requires ONNX
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f[2], _ = export_onnx(model, im, file, opset, train, dynamic, simplify)
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if xml: # OpenVINO
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f[3], _ = export_openvino(model, file, half)
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if coreml:
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f[3], _ = export_openvino(file, metadata, half)
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if coreml: # CoreML
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f[4], _ = export_coreml(model, im, file, int8, half)
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# TensorFlow Exports
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if any((saved_model, pb, tflite, edgetpu, tfjs)):
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if any((saved_model, pb, tflite, edgetpu, tfjs)): # TensorFlow formats
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if int8 or edgetpu: # TFLite --int8 bug https://github.com/ultralytics/yolov5/issues/5707
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check_requirements('flatbuffers==1.12') # required before `import tensorflow`
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assert not tflite or not tfjs, 'TFLite and TF.js models must be exported separately, please pass only one type.'
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assert not isinstance(model, ClassificationModel), 'ClassificationModel export to TF formats not yet supported.'
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f[5], model = export_saved_model(model.cpu(),
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im,
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file,
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dynamic,
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tf_nms=nms or agnostic_nms or tfjs,
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agnostic_nms=agnostic_nms or tfjs,
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topk_per_class=topk_per_class,
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topk_all=topk_all,
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iou_thres=iou_thres,
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conf_thres=conf_thres,
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keras=keras)
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f[5], s_model = export_saved_model(model.cpu(),
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im,
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file,
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dynamic,
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tf_nms=nms or agnostic_nms or tfjs,
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agnostic_nms=agnostic_nms or tfjs,
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topk_per_class=topk_per_class,
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topk_all=topk_all,
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iou_thres=iou_thres,
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conf_thres=conf_thres,
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keras=keras)
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if pb or tfjs: # pb prerequisite to tfjs
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f[6], _ = export_pb(model, file)
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f[6], _ = export_pb(s_model, file)
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if tflite or edgetpu:
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f[7], _ = export_tflite(model, im, file, int8 or edgetpu, data=data, nms=nms, agnostic_nms=agnostic_nms)
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f[7], _ = export_tflite(s_model, im, file, int8 or edgetpu, data=data, nms=nms, agnostic_nms=agnostic_nms)
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if edgetpu:
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f[8], _ = export_edgetpu(file)
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if tfjs:
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f[9], _ = export_tfjs(file)
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if paddle: # PaddlePaddle
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f[10], _ = export_paddle(model, im, file, metadata)
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# Finish
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f = [str(x) for x in f if x] # filter out '' and None
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