Issue with numpy?

[jhill1]

Running an example DeepDive sim and hit this error:

/home/jh1889/dd_env/lib/python3.12/site-packages/keras/src/layers/rnn/bidirectional.py:107: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.
  super().__init__(**kwargs)
Traceback (most recent call last):
  File "/home/jh1889/run_dd_config.py", line 55, in <module>
    run()
  File "/home/jh1889/run_dd_config.py", line 45, in run
    config_runner.run_config(args.config_file, wd=args.wd, CPU=args.cpu,
  File "/home/jh1889/dd_env/lib/python3.12/site-packages/deepdive/config_runner.py", line 165, in run_config
    model_tmp = run_model_training_from_config(config, feature_file=feature_file, label_file=label_file,
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/jh1889/dd_env/lib/python3.12/site-packages/deepdive/deepdiver_utilities.py", line 494, in run_model_training_from_config
    model = build_rnn(Xt_r,
            ^^^^^^^^^^^^^^^
  File "/home/jh1889/dd_env/lib/python3.12/site-packages/deepdive/rnn_builder.py", line 46, in build_rnn
    model.add(layers.Dense(dense_nodes[i],
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/jh1889/dd_env/lib/python3.12/site-packages/keras/src/layers/core/dense.py", line 102, in __init__
    raise ValueError(
ValueError: Received an invalid value for `units`, expected a positive integer. Received: units=64

Looks like with the latest numpy a np.int64(64) rather than a python int.

Simple fix is to change:

    for i in range(len(dense_nodes)):
        model.add(layers.Dense(dense_nodes[i],
                               activation=dense_act_f))

to

    for i in range(len(dense_nodes)):
        model.add(layers.Dense(int(dense_nodes[i]),
                               activation=dense_act_f))

in rnn_builder.py

My package list is:

Package            Version
------------------ -----------
absl-py            2.4.0
astunparse         1.6.3
certifi            2026.2.25
charset-normalizer 3.4.7
contourpy          1.3.3
cycler             0.12.1
DeepDive           1.0.28
flatbuffers        25.12.19
fonttools          4.62.1
gast               0.7.0
google-pasta       0.2.0
grpcio             1.80.0
h5py               3.14.0
idna               3.11
joblib             1.5.3
keras              3.14.0
kiwisolver         1.5.0
libclang           18.1.1
markdown-it-py     4.0.0
matplotlib         3.10.8
mdurl              0.1.2
ml_dtypes          0.5.4
namex              0.1.0
numpy              2.4.4
opt_einsum         3.4.0
optree             0.19.0
packaging          26.1
pandas             3.0.2
pillow             12.2.0
pip                24.0
protobuf           7.34.1
Pygments           2.20.0
pyparsing          3.3.2
python-dateutil    2.9.0.post0
requests           2.33.1
rich               15.0.0
scikit-learn       1.8.0
scipy              1.17.1
seaborn            0.13.2
setuptools         82.0.1
six                1.17.0
tensorflow         2.21.0
termcolor          3.3.0
threadpoolctl      3.6.0
typing_extensions  4.15.0
urllib3            2.6.3
wheel              0.46.3
wrapt              2.1.2