gluon2pytorch

Gluon to PyTorch model convertor with script generation.

Installation

git clone https://github.com/nerox8664/gluon2pytorch
cd gluon2pytorch
pip install -e . 

or you can use pip:

pip install gluon2pytorch

How to use

It's the convertor of Gluon graph to a Pytorch model file + weights.

Firstly, we need to load (or create) Gluon Hybrid model:

class ReLUTest(mx.gluon.nn.HybridSequential):
    def __init__(self):
        super(ReLUTest, self).__init__()
        from mxnet.gluon import nn
        with self.name_scope():
            self.conv1 = nn.Conv2D(3, 32)
            self.relu = nn.Activation('relu')

    def hybrid_forward(self, F, x):
        x = F.relu(self.relu(self.conv1(x)))
        return x


if __name__ == '__main__':
    net = ReLUTest()
    
    # Make sure it's hybrid and initialized
    net.hybridize()
    net.collect_params().initialize()

The next step - call the converter:

    pytorch_model = gluon2pytorch(net, [(1, 3, 224, 224)], dst_dir=None, pytorch_module_name='ReLUTest')

Finally, we can check the difference

    import torch
    input_np = np.random.uniform(-1, 1, (1, 3, 224, 224))

    gluon_output = net(mx.nd.array(input_np))
    pytorch_model.eval()
    pytorch_output = pytorch_model(torch.FloatTensor(input_np))
    check_error(gluon_output, pytorch_output)

Supported layers

Layers:

• Linear
• Conv2d
• ConvTranspose2d (Deconvolution)
• MaxPool2d
• AvgPool2d
• Global average pooling (as special case of AdaptiveAvgPool2d)
• BatchNorm2d*
• Padding2d (constant, reflection, replication)

Reshape:

• Flatten

Activations:

• ReLU
• LeakyReLU
• Sigmoid
• Softmax
• SELU

Element-wise:

• Addition
• Concatenation
• Subtraction
• Multiplication

Misc:

• clamp
• BilinearResize2D
• LRN

Classification models converted with gluon2pytorch

Model	Top1	Top5	Params	FLOPs	Source weights	Remarks
ResNet-10	37.09	15.55	5,418,792	892.62M	osmr's repo	Success
ResNet-12	35.86	14.46	5,492,776	1,124.23M	osmr's repo	Success
ResNet-14	32.85	12.41	5,788,200	1,355.64M	osmr's repo	Success
ResNet-16	30.68	11.10	6,968,872	1,586.95M	osmr's repo	Success
ResNet-18 x0.25	49.16	24.45	831,096	136.64M	osmr's repo	Success
ResNet-18 x0.5	36.54	14.96	3,055,880	485.22M	osmr's repo	Success
ResNet-18 x0.75	33.25	12.54	6,675,352	1,045.75M	osmr's repo	Success
ResNet-18	29.13	9.94	11,689,512	1,818.21M	osmr's repo	Success
ResNet-34	25.34	7.92	21,797,672	3,669.16M	osmr's repo	Success
ResNet-50	23.50	6.87	25,557,032	3,868.96M	osmr's repo	Success
ResNet-50b	22.92	6.44	25,557,032	4,100.70M	osmr's repo	Success
ResNet-101	21.66	5.99	44,549,160	7,586.30M	osmr's repo	Success
ResNet-101b	21.18	5.60	44,549,160	7,818.04M	osmr's repo	Success
ResNet-152	21.01	5.61	60,192,808	11,304.85M	osmr's repo	Success
ResNet-152b	20.54	5.37	60,192,808	11,536.58M	osmr's repo	Success
PreResNet-18	28.72	9.88	11,687,848	1,818.41M	osmr's repo	Success
PreResNet-34	25.88	8.11	21,796,008	3,669.36M	osmr's repo	Success
PreResNet-50	23.39	6.68	25,549,480	3,869.16M	osmr's repo	Success
PreResNet-50b	23.16	6.64	25,549,480	4,100.90M	osmr's repo	Success
PreResNet-101	21.45	5.75	44,541,608	7,586.50M	osmr's repo	Success
PreResNet-101b	21.73	5.88	44,541,608	7,818.24M	osmr's repo	Success
PreResNet-152	20.70	5.32	60,185,256	11,305.05M	osmr's repo	Success
PreResNet-152b	21.00	5.75	60,185,256	11,536.78M	Gluon Model Zoo	Success
PreResNet-200b	21.10	5.64	64,666,280	15,040.27M	tornadomeet/ResNet	Success
ResNeXt-101 (32x4d)	21.32	5.79	44,177,704	7,991.62M	Cadene's repo	Success
ResNeXt-101 (64x4d)	20.60	5.41	83,455,272	15,491.88M	Cadene's repo	Success
SE-ResNet-50	22.51	6.44	28,088,024	3,877.01M	Cadene's repo	Success
SE-ResNet-101	21.92	5.89	49,326,872	7,600.01M	Cadene's repo	Success
SE-ResNet-152	21.48	5.77	66,821,848	11,324.62M	Cadene's repo	Success
SE-ResNeXt-50 (32x4d)	21.06	5.58	27,559,896	4,253.33M	Cadene's repo	Success
SE-ResNeXt-101 (32x4d)	19.99	5.00	48,955,416	8,005.33M	Cadene's repo	Success
SENet-154	18.84	4.65	115,088,984	20,742.40M	Cadene's repo	Success
DenseNet-121	25.11	7.80	7,978,856	2,852.39M	Gluon Model Zoo	Success
DenseNet-161	22.40	6.18	28,681,000	7,761.25M	Gluon Model Zoo	Success
DenseNet-169	23.89	6.89	14,149,480	3,381.48M	Gluon Model Zoo	Success
DenseNet-201	22.71	6.36	20,013,928	4,318.75M	Gluon Model Zoo	Success
DPN-68	23.57	7.00	12,611,602	2,338.71M	Cadene's repo	Success
DPN-98	20.23	5.28	61,570,728	11,702.80M	Cadene's repo	Success
DPN-131	20.03	5.22	79,254,504	16,056.22M	Cadene's repo	Success
DarkNet Tiny	40.31	17.46	1,042,104	496.34M	osmr's repo	Success
DarkNet Ref	38.00	16.68	7,319,416	365.55M	osmr's repo	Success
SqueezeNet v1.0	40.97	18.96	1,248,424	828.30M	osmr's repo	Success
SqueezeNet v1.1	39.09	17.39	1,235,496	354.88M	osmr's repo	Success
SqueezeResNet v1.1	39.83	17.84	1,235,496	354.88M	osmr's repo	Success
ShuffleNetV2 x0.5	40.61	18.30	1,366,792	42.34M	osmr's repo	Success
ShuffleNetV2c x0.5	39.87	18.11	1,366,792	42.37M	tensorpack/tensorpack	Success
ShuffleNetV2 x1.0	33.76	13.22	2,278,604	147.92M	osmr's repo	Success
ShuffleNetV2c x1.0	30.74	11.38	2,279,760	148.85M	tensorpack/tensorpack	Success
ShuffleNetV2 x1.5	32.38	12.37	4,406,098	318.61M	osmr's repo	Success
ShuffleNetV2 x2.0	32.04	12.10	7,601,686	593.66M	osmr's repo	Success
108-MENet-8x1 (g=3)	43.62	20.30	654,516	40.64M	osmr's repo	Success
128-MENet-8x1 (g=4)	45.80	21.93	750,796	43.58M	clavichord93/MENet	Success
228-MENet-12x1 (g=3)	35.03	13.99	1,806,568	148.93M	clavichord93/MENet	Success
256-MENet-12x1 (g=4)	34.49	13.90	1,888,240	146.11M	clavichord93/MENet	Success
348-MENet-12x1 (g=3)	31.17	11.41	3,368,128	306.31M	clavichord93/MENet	Success
352-MENet-12x1 (g=8)	34.70	13.75	2,272,872	151.03M	clavichord93/MENet	Success
456-MENet-24x1 (g=3)	29.57	10.43	5,304,784	560.72M	clavichord93/MENet	Success
MobileNet x0.25	45.78	22.18	470,072	42.30M	osmr's repo	Success
MobileNet x0.5	36.12	14.81	1,331,592	152.04M	osmr's repo	Success
MobileNet x0.75	32.71	12.28	2,585,560	329.22M	Gluon Model Zoo	Success
MobileNet x1.0	29.25	10.03	4,231,976	573.83M	Gluon Model Zoo	Success
FD-MobileNet x0.25	56.19	31.38	383,160	12.44M	osmr's repo	Success
FD-MobileNet x0.5	42.62	19.69	993,928	40.93M	osmr's repo	Success
FD-MobileNet x1.0	35.95	14.72	2,901,288	146.08M	clavichord93/FD-MobileNet	Success
MobileNetV2 x0.25	48.89	25.24	1,516,392	32.22M	Gluon Model Zoo	Success
MobileNetV2 x0.5	35.51	14.64	1,964,736	95.62M	Gluon Model Zoo	Success
MobileNetV2 x0.75	30.82	11.26	2,627,592	191.61M	Gluon Model Zoo	Success
MobileNetV2 x1.0	28.51	9.90	3,504,960	320.19M	Gluon Model Zoo	Success
NASNet-A-Mobile	25.37	7.95	5,289,978	587.29M	Cadene's repo	Success
InceptionV3	21.22	5.59	23,834,568	5,746.72M	Gluon Model Zoo	Success
AirNet50-1x64d (r=2)	22.48	6.21	27,425,864	4,757.77M	soeaver/AirNet-PyTorch	Success
AirNet50-1x64d (r=16)	22.91	6.46	25,714,952	4,385.54M	soeaver/AirNet-PyTorch	Success
AirNeXt50-32x4d (r=2)	20.87	5.51	27,604,296	5,321.18M	soeaver/AirNet-PyTorch	Success
DiracNetV2-18	31.47	11.70	11,511,784	1,798.43M	szagoruyko/diracnets	Success
DiracNetV2-34	28.75	9.93	21,616,232	3,649.37M	szagoruyko/diracnets	Success
DARTS	26.70	8.74	4,718,752	537.64M	szagoruyko/diracnets	Success
PolyNet	19.10	4.52	95,366,600	34,768.84M	Cadene's repo	Success
ZfNet	?	?	?	?	osmr's repo	Success
FishNet-150	22.85	6.38	24,959,400	6,435.02M	osmr's repo	Success

Segmentation models converted with gluon2pytorch

Name	Model	pixAcc	mIoU	Source weights	Remarks
fcn_resnet101_coco	FCN	92.2	66.2	Gluon Model Zoo	Success
fcn_resnet101_voc	FCN	N/A	83.6	Gluon Model Zoo	Success

Code snippets

Look at the tests directory.

License

This software is covered by MIT License.