soeque1 opened a new issue #12844: ERROR parameter summary of lists layer URL: https://github.com/apache/incubator-mxnet/issues/12844 ## Description Error occurs when print_summary() related to lstm layer. ## Environment info (Required) ``` MXNet 1.3.1 Package used (Python/R/Scala/Julia): Python ``` Package used (Python/R/Scala/Julia): (I'm using ...) ## Error Message: (Paste the complete error message, including stack trace.) ``` IndexError Traceback (most recent call last) <ipython-input-5-d356a40b32a2> in <module> 1 mx.viz.print_summary( 2 model(mx.sym.var('data')), ----> 3 shape={'data':shape} 4 ) ~/python/venv/ngram_detectors/lib/python3.6/site-packages/mxnet/visualization.py in print_summary(symbol, shape, line_length, positions) 186 if key in shape_dict: 187 out_shape = shape_dict[key][1:] --> 188 total_params += print_layer_summary(nodes[i], out_shape) 189 if i == len(nodes) - 1: 190 print('=' * line_length) ~/python/venv/ngram_detectors/lib/python3.6/site-packages/mxnet/visualization.py in print_layer_summary(node, out_shape) 132 if key in shape_dict: 133 shape = shape_dict[key][1:] --> 134 pre_filter = pre_filter + int(shape[0]) 135 cur_param = 0 136 if op == 'Convolution': IndexError: tuple index out of range ``` ## Minimum reproducible example ``` import mxnet as mx model = mx.gluon.nn.HybridSequential() with model.name_scope(): model.add(mx.gluon.nn.Embedding(30, 10)) model.add(mx.gluon.rnn.LSTM(20)) model.add(mx.gluon.nn.Dense(5, flatten=False)) model.hybridize() shape = (2,3) mx.viz.print_summary( model(mx.sym.var('data')), shape={'data':shape} ) ``` ## What have you tried to solve it? 1. Add logic for lstm, RNN, and so on layers related to RNN 2. Add Exception for error
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