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intel-analytics / analytics-zoo

Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray
https://analytics-zoo.readthedocs.io/
Apache License 2.0
16 stars 3 forks source link

resnet50: torchnet's inference result is not the same with pytorch's result #1047

Closed qiuxin2012 closed 5 years ago

qiuxin2012 commented 5 years ago

test code

import torchvision
import numpy as np
from zoo.pipeline.api.net.torch_net import TorchNet

from zoo.common.nncontext import init_nncontext
sc = init_nncontext("Object Detection Example")

input = np.random.rand(1, 3, 224, 224)

model = torchvision.models.resnet18().eval()
net = TorchNet.from_pytorch(model, [1, 3, 224, 224])

result = net.predict(input)
print(result.collect())

import torch
with torch.no_grad():
    print(model(torch.Tensor(input)))

torchnet's result:

[array([ 3.74878109e-01, -1.31922567e+00, -8.85901034e-01, -7.12347269e-01,
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pytorch result:

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jason-dai commented 5 years ago

Can you try libtorch c++ code to verify that libtorch can get the correct result?

qiuxin2012 commented 5 years ago

fixed by intel-analytics/analytics-zoo#1481