when running with built mxnet-1.7 with head of v1.7.x; if I create a model with even number of channels in batch norm, I got the is_view check failure when using mkldnn.
Error Messagedev-dsk-haohuw-2c-3d588fe6 % MKLDNN_VERBOSE=1 bte python minimum_repro.py
input channel of 45
dnnl_verbose,info,oneDNN v1.6.0 (commit N/A)
dnnl_verbose,info,cpu,runtime:sequential
dnnl_verbose,info,cpu,isa:Intel AVX2
dnnl_verbose,info,gpu,runtime:none
dnnl_verbose,exec,cpu,convolution,gemm:jit,forward_inference,src_f32::blocked:abcde:f0 wei_f32::blocked:abcde:f0 bia_undef::undef::f0 dst_f32::blocked:abcde:f0,,alg:convolution_direct,mb1_ic3oc45_id8od8kd1sd1dd0pd0_ih160oh80kh7sh2dh0ph3_iw160ow80kw7sw2dw0pw3,46.7029
dnnl_verbose,exec,cpu,batch_normalization,ncsp_bnorm:any,forward_inference,data_f32::blocked:abcd:f0 diff_undef::undef::f0,,flags:GS,mb1ic45ih1iw51200,8.98315
input channel of 45, (1, 45, 8, 80, 80)
input channel of 64
dnnl_verbose,exec,cpu,reorder,jit:uni,undef,src_f32::blocked:abcde:f0 dst_f32::blocked:Acdeb8a:f0,,,64x3x1x7x7,0.0170898
dnnl_verbose,exec,cpu,convolution,jit:avx2,forward_inference,src_f32::blocked:abcde:f0 wei_f32::blocked:Acdeb8a:f0 bia_undef::undef::f0 dst_f32::blocked:aBcde8b:f0,,alg:convolution_direct,mb1_ic3oc64_id8od8kd1sd1dd0pd0_ih160oh80kh7sh2dh0ph3_iw160ow80kw7sw2dw0pw3,17.5981
dnnl_verbose,exec,cpu,reorder,jit:uni,undef,src_f32::blocked:abcde:f0 dst_f32::blocked:Acdeb8a:f0,,,64x3x1x7x7,0.0258789
Traceback (most recent call last):
File "minimum_repro.py", line 53, in <module>
out = net(input_data).asnumpy()
File "/home/haohuw/vision-only-workspace/c2h_mainline/env/IhmPoseStateLib-1.0/test-runtime/lib/python3.6/site-packages/mxnet/ndarray/ndarray.py", line 2566, in asnumpy
ctypes.c_size_t(data.size)))
File "/home/haohuw/vision-only-workspace/c2h_mainline/env/IhmPoseStateLib-1.0/test-runtime/lib/python3.6/site-packages/mxnet/base.py", line 246, in check_call
raise get_last_ffi_error()
mxnet.base.MXNetError: Traceback (most recent call last):
File "/home/haohuw/vision-only-workspace/c2h_mainline/src/IhmMXNet/build/private/src/src/ndarray/ndarray.cc", line 650
MXNetError: Check failed: !is_view:
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
Steps to reproduceimport logging
import os
from mxnet import init
from mxnet.context import cpu
from mxnet.gluon import nn
from mxnet.gluon.block import HybridBlock
from mxnet.gluon.nn import BatchNorm
import mxnet as mx
class BuggyModel(HybridBlock):
def __init__(
self,
channels,
norm_layer=BatchNorm,
norm_kwargs=None,
in_channels=3,
**kwargs
):
super(BuggyModel, self).__init__(**kwargs)
self.in_channels = in_channels
with self.name_scope():
self.conv1 = nn.Conv3D(
in_channels=self.in_channels,
channels=channels,
kernel_size=(1, 7, 7),
strides=(1, 2, 2),
padding=(0, 3, 3),
use_bias=False,
)
self.bn1 = norm_layer(in_channels=channels, **({} if norm_kwargs is None else norm_kwargs))
def hybrid_forward(self, F, x):
"""Hybrid forward of R2+1D net"""
x = self.conv1(x)
x = self.bn1(x)
return x
print(f"input channel of 45")
net = BuggyModel(channels=45)
net.initialize(init=init.Constant(1))
input_data = mx.nd.zeros((1, 3, 8, 160, 160), ctx=mx.cpu())
out = net(input_data).asnumpy()
print(f"input channel of 45, {out.shape}")
print(f"input channel of 64")
net = BuggyModel(channels=64)
net.initialize(init=init.Constant(1))
input_data = mx.nd.zeros((1, 3, 8, 160, 160), ctx=mx.cpu())
out = net(input_data).asnumpy()
print(f"input channel of 64, {out.shape}")
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
curl --retry 10 -s https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py | python
dev-dsk-haohuw-2c-3d588fe6 % curl --retry 10 -s https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py | python
----------Python Info----------
Version : 3.6.11
Compiler : GCC 7.5.0
Build : ('default', 'Sep 11 2020 22:03:53')
Arch : ('64bit', 'ELF')
------------Pip Info-----------
No corresponding pip install for current python.
----------MXNet Info-----------
No MXNet installed.
----------System Info----------
Platform : Linux-4.9.217-0.1.ac.205.84.332.metal1.x86_64-x86_64-with-redhat-5.3-Tikanga
system : Linux
node : dev-dsk-haohuw-2c-3d588fe6.us-west-2.amazon.com
release : 4.9.217-0.1.ac.205.84.332.metal1.x86_64
version : #1 SMP Thu Apr 2 15:19:24 UTC 2020
----------Hardware Info----------
machine : x86_64
processor : x86_64
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 8
On-line CPU(s) list: 0-7
Thread(s) per core: 2
Core(s) per socket: 4
Socket(s): 1
NUMA node(s): 1
Vendor ID: GenuineIntel
CPU family: 6
Model: 79
Stepping: 1
CPU MHz: 2699.945
BogoMIPS: 4600.13
Hypervisor vendor: Xen
Virtualization type: full
L1d cache: 32K
L1i cache: 32K
L2 cache: 256K
L3 cache: 46080K
NUMA node0 CPU(s): 0-7
----------Network Test----------
Setting timeout: 10
Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0018 sec, LOAD: 0.5492 sec.
Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.0429 sec, LOAD: 0.1730 sec.
Error open Gluon Tutorial(cn): https://zh.gluon.ai, <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:852)>, DNS finished in 0.34314703941345215 sec.
Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.0204 sec, LOAD: 0.1066 sec.
Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0234 sec, LOAD: 0.4174 sec.
Error open Conda: https://repo.continuum.io/pkgs/free/, HTTP Error 403: Forbidden, DNS finished in 0.010480880737304688 sec.
----------Environment----------
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4