use torchview to visualize the openmmlab 2.0 model
400+ mmyolo mmdetection models has been visualized, mmrotate、mmclassification models are coming soon.
if you want to visualize your model, you can use the model_visual.ipynb.
# Copyright (c) OpenMMLab. All rights reserved.
import argparse
import torch
from mmengine import Config
from functools import partial
# if you want
from mmrotate.registry import MODELS
from mmrotate.utils import register_all_modules
register_all_modules()
# from mmdet.registry import MODELS
# from mmdet.utils import register_all_modules
# register_all_modules()
import graphviz
from mmengine.runner import Runner
from torchview import draw_graph
from torchinfo import summary
graphviz.set_default_format('svg')
config = '../mmrotate/configs/rotated_retinanet/rotated-retinanet-rbox-le90_r50_fpn_1x_dota.py'
graph_path = config.replace('mmrotate','model_visual/mmrotate')
cfg = Config.fromfile(config)
dataloader = Runner.build_dataloader(cfg.val_dataloader)
for idx, data_batch in enumerate(dataloader):
print(idx, data_batch)
break
model = MODELS.build(cfg.model)
_forward = model.forward
data = model.data_preprocessor(data_batch)
model.forward = partial(_forward, data_samples=data['data_samples'])
summary(model, data['inputs'].shape, depth=3)
# summary(model, (1, 3, 1024, 1024), depth=3)
model_graph = draw_graph(model, input_size=data['inputs'].shape)
model_graph.visual_graph
# model_graph.visual_graph.render(filename=graph_path, view=False, cleanup=True)
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