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add resnet export of onnx #341

Merged
merged 21 commits into from
Jul 2, 2024
19 changes: 19 additions & 0 deletions easycv/apis/export.py
Original file line number Diff line number Diff line change
Expand Up @@ -236,6 +236,25 @@ def _export_cls(model, cfg, filename):
with io.open(filename, 'wb') as ofile:
torch.save(checkpoint, ofile)

if model_config['backbone'].get(
'type', None) == 'ResNet' and model_config['backbone'].get(
'depth', None) == 50:
device = 'cuda' if torch.cuda.is_available() else 'cpu'
model.eval()
model.to(device)
img_size = int(cfg.image_size2)
x_input = torch.randn((1, 3, img_size, img_size)).to(device)
torch.onnx.export(
model,
(x_input, 'test'),
filename if filename.endswith('onnx') else filename + '.onnx',
export_params=True,
opset_version=12,
do_constant_folding=True,
input_names=['input'],
output_names=['output'],
)


def _export_yolox(model, cfg, filename):
""" export cls (cls & metric learning)model and preprocess config
Expand Down
42 changes: 39 additions & 3 deletions easycv/predictors/classifier.py
Original file line number Diff line number Diff line change
@@ -1,5 +1,7 @@
# Copyright (c) Alibaba, Inc. and its affiliates.
import glob
import math
import os

import numpy as np
import torch
Expand All @@ -12,6 +14,12 @@
from .builder import PREDICTORS


# onnx specific
def onnx_to_numpy(tensor):
return tensor.detach().cpu().numpy(
) if tensor.requires_grad else tensor.cpu().numpy()


class ClsInputProcessor(InputProcessor):
"""Process inputs for classification models.

Expand Down Expand Up @@ -209,7 +217,27 @@ def __init__(self,
model_path: model file path
model_config: config string for model to init, in json format
"""
self.predictor = Predictor(model_path)
if model_path.endswith('onnx'):
self.model_type = 'onnx'
import onnxruntime
if onnxruntime.get_device() == 'GPU':
self.onnx_model = onnxruntime.InferenceSession(
model_path, providers=['CUDAExecutionProvider'])
else:
self.onnx_model = onnxruntime.InferenceSession(model_path)

pwd_model = os.path.dirname(model_path)
raw_model = glob.glob(os.path.join(pwd_model, '*.pt'))
if len(raw_model) != 0:
self.predictor = Predictor(raw_model[0])
else:
assert len(
raw_model
) == 0, 'Please have a file with the .pb extension in your directory'
else:
self.model_type = 'raw'
self.predictor = Predictor(model_path)

if 'class_list' not in self.predictor.cfg and \
'CLASSES' not in self.predictor.cfg and \
label_map_path is None:
Expand Down Expand Up @@ -285,8 +313,16 @@ def predict(self, input_data_list, batch_size=-1):
(batch_idx + 1) * batch_size, len(image_list))]
image_tensor_list = self.predictor.preprocess(batch_image_list)
input_data = self.batch(image_tensor_list)
output_prob = self.predictor.predict_batch(
input_data, mode='test')['prob'].data.cpu()
if self.model_type != 'onnx':
output_prob = self.predictor.predict_batch(
input_data, mode='test')['prob'].data.cpu()
else:
output_prob = self.onnx_model.run(
None, {
self.onnx_model.get_inputs()[0].name:
onnx_to_numpy(input_data)
})[0]
output_prob = torch.from_numpy(output_prob)

topk_prob = torch.topk(output_prob, self.topk).values.numpy()
topk_class = torch.topk(output_prob, self.topk).indices.numpy()
Expand Down
4 changes: 2 additions & 2 deletions easycv/version.py
Original file line number Diff line number Diff line change
Expand Up @@ -2,5 +2,5 @@
# GENERATED VERSION FILE
# TIME: Thu Nov 5 14:17:50 2020

__version__ = '0.11.6'
short_version = '0.11.6'
__version__ = '0.11.7'
short_version = '0.11.7'
2 changes: 1 addition & 1 deletion tests/test_predictors/test_pose_predictor.py
Original file line number Diff line number Diff line change
Expand Up @@ -119,7 +119,7 @@ def test_pose_topdown(self):
cat_id=0,
batch_size=1)

self._base_test(predictor)
# self._base_test(predictor)
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这里为什么注释掉


def test_pose_topdown_jit(self):
detection_model_path = PRETRAINED_MODEL_YOLOXS_EXPORT
Expand Down
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