zhhoper commented on issue #17231: cannot quantization example URL: https://github.com/apache/incubator-mxnet/issues/17231#issuecomment-571373823 @ZhennanQin I tried to set calib-mode to 'naive', met the same error. Error message as follows INFO:logger:Namespace(batch_size=32, calib_dataset='data/val_256_q90.rec', calib_mode='naive', data_nthreads=60, enable_calib_quantize=True, epoch=0, exclude_first_conv=False, image_shape='3,224,224', label_name='softmax_label', model='resnet50_v1', no_pretrained=False, num_calib_batches=10, quantized_dtype='auto', quiet=False, shuffle_chunk_seed=3982304, shuffle_dataset=True, shuffle_seed=48564309) INFO:logger:shuffle_dataset=True INFO:logger:calibration mode set to naive INFO:logger:Get pre-trained model from MXNet or Gluoncv modelzoo. INFO:logger:If you want to use custom model, please set --no-pretrained. INFO:logger:model resnet50_v1 is converted from GluonCV INFO:logger:Converting model from Gluon-CV ModelZoo resnet50_v1... into path /home/ubuntu/software/incubator-mxnet/example/quantization/model /home/ubuntu/anaconda3/envs/mxnet_0.15/lib/python3.6/site-packages/mxnet-1.6.0-py3.6.egg/mxnet/module/base_module.py:67: UserWarning: Data provided by label_shapes don't match names specified by label_names ([] vs. ['softmax_label']) warnings.warn(msg) [00:17:25] ../src/executor/graph_executor.cc:1982: Subgraph backend MKLDNN is activated. INFO:logger:batch size = 32 for calibration INFO:logger:number of batches = 10 for calibration INFO:logger:These layers have been excluded [] INFO:logger:label_name = softmax_label INFO:logger:Input data shape = (3, 224, 224) INFO:logger:rgb_mean = 123.68,116.779,103.939 INFO:logger:rgb_std = 58.393, 57.12, 57.375 INFO:logger:Creating ImageRecordIter for reading calibration dataset [00:17:26] ../src/io/iter_image_recordio_2.cc:178: ImageRecordIOParser2: data/val_256_q90.rec, use 16 threads for decoding.. Segmentation fault: 11
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