CodePlay2016 opened a new issue #11794: fail to quantize custom symbols exported from hybrid block URL: https://github.com/apache/incubator-mxnet/issues/11794 ## Description when i quantized my custom symbol exported from hybrid block use the [quantization tool](https://github.com/apache/incubator-mxnet/tree/master/example/quantization), there will always be a duplicated output node which will lead to an error when i bind the module. ## Environment info (Required) ``` ----------Python Info---------- ('Version :', '2.7.12') ('Compiler :', 'GCC 5.4.0 20160609') ('Build :', ('default', 'Nov 19 2016 06:48:10')) ('Arch :', ('64bit', 'ELF')) ------------Pip Info----------- ('Version :', '10.0.1') ('Directory :', '/usr/local/lib/python2.7/dist-packages/pip') ----------MXNet Info----------- ('Version :', '1.2.0') ('Directory :', '/usr/local/lib/python2.7/dist-packages/mxnet') ('Commit Hash :', '297c64fd2ee404612aa3ecc880b940fb2538039c') ----------System Info---------- ('Platform :', 'Linux-4.4.0-87-generic-x86_64-with-Ubuntu-16.04-xenial') ('system :', 'Linux') ('node :', 'BoHong') ('release :', '4.4.0-87-generic') ('version :', '#110-Ubuntu SMP Tue Jul 18 12:55:35 UTC 2017') ----------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): 48 On-line CPU(s) list: 0-47 Thread(s) per core: 2 Core(s) per socket: 12 Socket(s): 2 NUMA node(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 79 Model name: Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz Stepping: 1 CPU MHz: 2508.429 CPU max MHz: 2900.0000 CPU min MHz: 1200.0000 BogoMIPS: 4401.31 Virtualization: VT-x L1d cache: 32K L1i cache: 32K L2 cache: 256K L3 cache: 30720K NUMA node0 CPU(s): 0-11,24-35 NUMA node1 CPU(s): 12-23,36-47 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf eagerfpu pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch epb intel_pt tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdseed adx smap xsaveopt cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts ----------Network Test---------- Setting timeout: 10 Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0190 sec, LOAD: 1.5759 sec. Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0134 sec, LOAD: 9.3883 sec. Timing for FashionMNIST: https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz, DNS: 0.2021 sec, LOAD: 1.9859 sec. Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.0132 sec, LOAD: 1.3754 sec. Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.4865 sec, LOAD: 3.5648 sec. Timing for Gluon Tutorial(cn): https://zh.gluon.ai, DNS: 0.4228 sec, LOAD: 1.7980 sec. ``` Package used (Python/R/Scala/Julia): i'm using Python MXNet commit hash: (Paste the output of `git rev-parse HEAD` here.) ## Error Message: ``` Traceback (most recent call last): File "/opt/pycharm-community-2017.3.2/helpers/pydev/pydevd.py", line 1668, in <module> main() File "/opt/pycharm-community-2017.3.2/helpers/pydev/pydevd.py", line 1662, in main globals = debugger.run(setup['file'], None, None, is_module) File "/opt/pycharm-community-2017.3.2/helpers/pydev/pydevd.py", line 1072, in run pydev_imports.execfile(file, globals, locals) # execute the script File "/home/hfq/model_compress/prune/1611.06440/prune_mx_face/quantization.py", line 49, in <module> mod.bind(data_shapes=[('data', (32, 3, 96, 112))],for_training=False) File "/usr/local/lib/python2.7/dist-packages/mxnet/module/module.py", line 430, in bind state_names=self._state_names) File "/usr/local/lib/python2.7/dist-packages/mxnet/module/executor_group.py", line 265, in __init__ self.bind_exec(data_shapes, label_shapes, shared_group) File "/usr/local/lib/python2.7/dist-packages/mxnet/module/executor_group.py", line 361, in bind_exec shared_group)) File "/usr/local/lib/python2.7/dist-packages/mxnet/module/executor_group.py", line 639, in _bind_ith_exec shared_buffer=shared_data_arrays, **input_shapes) File "/usr/local/lib/python2.7/dist-packages/mxnet/symbol/symbol.py", line 1519, in simple_bind raise RuntimeError(error_msg) RuntimeError: simple_bind error. Arguments: data: (32, 3, 96, 112) Error in operator spherenet200_dense0_fwd_dequantize: Shape inconsistent, Provided = [10574,512], inferred shape=[1] ``` ## Minimum reproducible example ``` excluded_sym_names = ['spherenet200_conv0_fwd'] # exclude the first layer for name in sym.get_internals().list_outputs(): if 'residual' in name: excluded_sym_names.append(name[:-7]) cqsym, qarg_params, aux_params = quantize_model(sym=sym, arg_params=arg_params, aux_params=aux_params, ctx=ctx,calib_mode='none', excluded_sym_names=excluded_sym_names) cqnodes = cqsym.get_internals().list_outputs() for ii, name in enumerate(cqnodes): print ii, name if name == 'spherenet200_dense0_fwd_dequantize_output': cqfeatures = cqsym.get_internals()[:ii+1] break mod = mx.mod.Module(symbol=cqfeatures, context=ctx,label_names=None) mod.bind(data_shapes=[('data', (32, 3, 96, 112))],for_training=False) ``` ## Steps to reproduce i have tried to replace the custom blocks with the original mxnet gluon block (use gluon.nn.LeakyReLU instead of custom PReLU), which could solve this problem, but i need that custom layer, so this is not a feasible solution to me.
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