TriLoo opened a new issue #15635: gluon.nn.Conv2DTranspose() may have a problem working with MKLDNN data ? URL: https://github.com/apache/incubator-mxnet/issues/15635 `mxnet version`: 1.5.0 `OS`: Centos 7.2 `Python`: 3.6 `CPU`: Xeon E5-2650 v4 Following code can reproduce this bug on my server: ```python import mxnet as mx from mxnet import gluon class VerifyConcatMKL(gluon.HybridBlock): def __init__(self, **kwargs): super(VerifyConcatMKL, self).__init__(**kwargs) self.conv = gluon.nn.Conv2D(10, 3, 1, 1) self.conv1 = gluon.nn.Conv2D(channels=128, kernel_size=3, strides=1, padding=1) self.deconv1 = gluon.nn.Conv2DTranspose(64, 4, 2, 1) def hybrid_forward(self, F, x, *args, **kwargs): feat = self.conv(x) output = self.conv1(feat) output = self.deconv1(output) return output net = VerifyConcatMKL() net.initialize() data = mx.nd.ones((1, 3, 10, 10)) pred = net(data) print(pred) . # raise an error ``` The error info is: ``` mxnet.base.MXNetError: [13:19:25] src/ndarray/ndarray.cc:752: Check failed: !IsMKLDNNData(): We can't generate TBlob for MKLDNN data. Please use Reorder2Default() to generate a new NDArray first ``` **What I found:** 1. if the `Conv2DTranspose()` after another `Conv2D()`, one output channel of these two operators must less than 24, for example ```Python self.conv1 = gluon.nn.Conv2D(channels=23, kernel_size=3, strides=1, padding=1) self.deconv1 = gluon.nn.Conv2DTranspose(64, 4, 2, 1) ``` works fine. 2. if the `Conv2DTranspose()` calculate the features before the `Conv2D`, this error not happen!
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