How to train model with LinkedIn leak ?

[semeniak1997]

I unpacked the "LinkedIn leak" archive into the "/data" directory and renamed it to train.txt. Launched with the following command:
python3 train.py --output-dir output --training-data data/train.txt
And throws the following error:
During handling of the above exception, another exception occurred: Traceback (most recent call last): File "train.py", line 103, in <module> disc_fake = models.Discriminator(fake_inputs, args.seq_length, args.layer_dim, len(charmap)) File "/share/home/nikita/devel/PassGAN/models.py", line 35, in Discriminator output = lib.ops.conv1d.Conv1D('Discriminator.Input', input_dim, layer_dim, 1, output) File "/share/home/nikita/devel/PassGAN/tflib/ops/conv1d.py", line 92, in Conv1D padding='SAME' File "/home/nikita/.local/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 574, in new_func return func(*args, **kwargs) File "/home/nikita/.local/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 574, in new_func return func(*args, **kwargs) File "/home/nikita/.local/lib/python3.6/site-packages/tensorflow/python/ops/nn_ops.py", line 3482, in conv1d data_format=data_format) File "/home/nikita/.local/lib/python3.6/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 1026, in conv2d data_format=data_format, dilations=dilations, name=name) File "/home/nikita/.local/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper op_def=op_def) File "/home/nikita/.local/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func return func(*args, **kwargs) File "/home/nikita/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3300, in create_op op_def=op_def) File "/home/nikita/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1823, in __init__ control_input_ops) File "/home/nikita/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1662, in _create_c_op raise ValueError(str(e)) ValueError: Shape must be rank 4 but is rank 3 for 'Discriminator.Input_1/conv1d/Conv2D' (op: 'Conv2D') with input shapes: [64,1,10], [1,1,1,128].

P.S. sample rockyou traind successful