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A Python library for building atomic neural networks

Home Page: https://teoroo-cmc.github.io/PiNN

License: BSD 3-Clause "New" or "Revised" License

Dockerfile 0.16% Python 96.09% Nextflow 3.75%

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cannot run LJ example

lj.zip
I tried to run the attached LJ example (tensorflow 2.9.1, python 3.8.12) but received the following error

WARNING:tensorflow:From /home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/training/training_util.py:396: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.
Instructions for updating:
Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.
WARNING:tensorflow:From /home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/training/training_util.py:396: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.
Instructions for updating:
Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.
2022-11-16 16:21:11.919525: E tensorflow/stream_executor/cuda/cuda_driver.cc:271] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected
WARNING:tensorflow:From /home/hellstrom/software/PiNN/pinn/io/numpy.py:33: calling DatasetV2.from_generator (from tensorflow.python.data.ops.dataset_ops) with output_types is deprecated and will be removed in a future version.
Instructions for updating:
Use output_signature instead
WARNING:tensorflow:From /home/hellstrom/software/PiNN/pinn/io/numpy.py:33: calling DatasetV2.from_generator (from tensorflow.python.data.ops.dataset_ops) with output_types is deprecated and will be removed in a future version.
Instructions for updating:
Use output_signature instead
WARNING:tensorflow:From /home/hellstrom/software/PiNN/pinn/io/numpy.py:33: calling DatasetV2.from_generator (from tensorflow.python.data.ops.dataset_ops) with output_shapes is deprecated and will be removed in a future version.
Instructions for updating:
Use output_signature instead
WARNING:tensorflow:From /home/hellstrom/software/PiNN/pinn/io/numpy.py:33: calling DatasetV2.from_generator (from tensorflow.python.data.ops.dataset_ops) with output_shapes is deprecated and will be removed in a future version.
Instructions for updating:
Use output_signature instead
3144 trainable vaiabless, training with float32 precision.
Traceback (most recent call last):
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1377, in _do_call
    return fn(*args)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1360, in _run_fn
    return self._call_tf_sessionrun(options, feed_dict, fetch_list,
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1453, in _call_tf_sessionrun
    return tf_session.TF_SessionRun_wrapper(self._session, options, feed_dict,
tensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [300,8] vs. [299,8]
	 [[{{node TRAIN_OP/gradients/pi_net/res_update/add_grad/BroadcastGradientArgs}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "Learn_LJ_potential.py", line 139, in <module>
    tf.estimator.train_and_evaluate(model, train_spec, eval_spec)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/training.py", line 504, in train_and_evaluate
    return executor.run()
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/training.py", line 645, in run
    return self.run_local()
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/training.py", line 742, in run_local
    self._estimator.train(
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 360, in train
    loss = self._train_model(input_fn, hooks, saving_listeners)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1186, in _train_model
    return self._train_model_default(input_fn, hooks, saving_listeners)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1217, in _train_model_default
    return self._train_with_estimator_spec(estimator_spec, worker_hooks,
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1533, in _train_with_estimator_spec
    _, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss])
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/training/monitored_session.py", line 782, in run
    return self._sess.run(
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/training/monitored_session.py", line 1311, in run
    return self._sess.run(
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/training/monitored_session.py", line 1416, in run
    raise six.reraise(*original_exc_info)
  File "/home/hellstrom/adfhome/bin.gnu/python3.8/lib/python3.8/site-packages/six.py", line 719, in reraise
    raise value
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/training/monitored_session.py", line 1401, in run
    return self._sess.run(*args, **kwargs)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/training/monitored_session.py", line 1469, in run
    outputs = _WrappedSession.run(
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/training/monitored_session.py", line 1232, in run
    return self._sess.run(*args, **kwargs)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 967, in run
    result = self._run(None, fetches, feed_dict, options_ptr,
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1190, in _run
    results = self._do_run(handle, final_targets, final_fetches,
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1370, in _do_run
    return self._do_call(_run_fn, feeds, fetches, targets, options,
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/client/session.py", line 1396, in _do_call
    raise type(e)(node_def, op, message)  # pylint: disable=no-value-for-parameter
tensorflow.python.framework.errors_impl.InvalidArgumentError: Graph execution error:

Detected at node 'TRAIN_OP/gradients/pi_net/res_update/add_grad/BroadcastGradientArgs' defined at (most recent call last):
    File "Learn_LJ_potential.py", line 139, in <module>
      tf.estimator.train_and_evaluate(model, train_spec, eval_spec)
    File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/training.py", line 504, in train_and_evaluate
      return executor.run()
    File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/training.py", line 645, in run
      return self.run_local()
    File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/training.py", line 742, in run_local
      self._estimator.train(
    File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 360, in train
      loss = self._train_model(input_fn, hooks, saving_listeners)
    File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1186, in _train_model
      return self._train_model_default(input_fn, hooks, saving_listeners)
    File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1214, in _train_model_default
      estimator_spec = self._call_model_fn(features, labels, ModeKeys.TRAIN,
    File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1174, in _call_model_fn
      model_fn_results = self._model_fn(features=features, **kwargs)
    File "/home/hellstrom/software/PiNN/pinn/models/potential.py", line 67, in potential_model
      train_op = get_train_op(params['optimizer'], metrics, tvars,
    File "/home/hellstrom/software/PiNN/pinn/utils.py", line 136, in named_layer
      return func(*args, **kwargs)
    File "/home/hellstrom/software/PiNN/pinn/models/base.py", line 101, in get_train_op
      grads = tf.gradients(loss, tvars)
Node: 'TRAIN_OP/gradients/pi_net/res_update/add_grad/BroadcastGradientArgs'
Incompatible shapes: [300,8] vs. [299,8]
	 [[{{node TRAIN_OP/gradients/pi_net/res_update/add_grad/BroadcastGradientArgs}}]]

Original stack trace for 'TRAIN_OP/gradients/pi_net/res_update/add_grad/BroadcastGradientArgs':
  File "Learn_LJ_potential.py", line 139, in <module>
    tf.estimator.train_and_evaluate(model, train_spec, eval_spec)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/training.py", line 504, in train_and_evaluate
    return executor.run()
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/training.py", line 645, in run
    return self.run_local()
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/training.py", line 742, in run_local
    self._estimator.train(
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 360, in train
    loss = self._train_model(input_fn, hooks, saving_listeners)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1186, in _train_model
    return self._train_model_default(input_fn, hooks, saving_listeners)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1214, in _train_model_default
    estimator_spec = self._call_model_fn(features, labels, ModeKeys.TRAIN,
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1174, in _call_model_fn
    model_fn_results = self._model_fn(features=features, **kwargs)
  File "/home/hellstrom/software/PiNN/pinn/models/potential.py", line 67, in potential_model
    train_op = get_train_op(params['optimizer'], metrics, tvars,
  File "/home/hellstrom/software/PiNN/pinn/utils.py", line 136, in named_layer
    return func(*args, **kwargs)
  File "/home/hellstrom/software/PiNN/pinn/models/base.py", line 101, in get_train_op
    grads = tf.gradients(loss, tvars)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/ops/gradients_impl.py", line 311, in gradients_v2
    return gradients_util._GradientsHelper(
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/ops/gradients_util.py", line 695, in _GradientsHelper
    in_grads = _MaybeCompile(grad_scope, op, func_call,
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/ops/gradients_util.py", line 328, in _MaybeCompile
    return grad_fn()  # Exit early
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/ops/gradients_util.py", line 696, in <lambda>
    lambda: grad_fn(op, *out_grads))
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/ops/math_grad.py", line 1302, in _AddGrad
    SmartBroadcastGradientArgs(x, y, grad))
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/ops/math_grad.py", line 106, in SmartBroadcastGradientArgs
    rx, ry = gen_array_ops.broadcast_gradient_args(sx, sy)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/ops/gen_array_ops.py", line 771, in broadcast_gradient_args
    _, _, _op, _outputs = _op_def_library._apply_op_helper(
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/framework/op_def_library.py", line 797, in _apply_op_helper
    op = g._create_op_internal(op_type_name, inputs, dtypes=None,
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/framework/ops.py", line 3754, in _create_op_internal
    ret = Operation(
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/framework/ops.py", line 2133, in __init__
    self._traceback = tf_stack.extract_stack_for_node(self._c_op)

...which was originally created as op 'pi_net/res_update/add', defined at:
  File "Learn_LJ_potential.py", line 139, in <module>
    tf.estimator.train_and_evaluate(model, train_spec, eval_spec)
[elided 6 identical lines from previous traceback]
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow_estimator/python/estimator/estimator.py", line 1174, in _call_model_fn
    model_fn_results = self._model_fn(features=features, **kwargs)
  File "/home/hellstrom/software/PiNN/pinn/models/potential.py", line 58, in potential_model
    pred = network(features)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler
    return fn(*args, **kwargs)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/keras/engine/training.py", line 490, in __call__
    return super().__call__(*args, **kwargs)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/keras/engine/base_layer_v1.py", line 763, in __call__
    outputs = call_fn(cast_inputs, *args, **kwargs)
  File "/home/hellstrom/software/PiNN/pinn/networks/pinet.py", line 196, in call
    for i in range(self.depth):
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/autograph/operators/control_flow.py", line 449, in for_stmt
    _py_for_stmt(iter_, extra_test, body, None, None)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/autograph/operators/control_flow.py", line 498, in _py_for_stmt
    body(target)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/autograph/operators/control_flow.py", line 464, in protected_body
    original_body(protected_iter)
  File "/home/hellstrom/software/PiNN/pinn/networks/pinet.py", line 199, in call
    tensors['prop'] = self.res_update[i]([tensors['prop'], prop])
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/keras/engine/base_layer_v1.py", line 763, in __call__
    outputs = call_fn(cast_inputs, *args, **kwargs)
  File "/home/hellstrom/software/PiNN/pinn/networks/pinet.py", line 128, in call
    return self.transform(old) + new
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/util/traceback_utils.py", line 150, in error_handler
    return fn(*args, **kwargs)
  File "/home/hellstrom/.scm/python/AMS2022.2.venv/lib/python3.8/site-packages/tensorflow/python/ops/math_ops.py", line 1406, in binary_op_wrapper
    return func(x, y, name=name)

'FlatMapDataset' object has no attribute 'make_one_shot_iterator

Trying to go though the examples in the documentation, I ran into this error with Loading data.

when I run the command:

datalist = [Atoms(elem) for elem in ['Cu', 'Ag', 'Au']]
dataset = load_ase_list(datalist)['train']
"d = dataset.make_one_shot_iterator().get_next()"
error:
AttributeError: 'FlatMapDataset' object has no attribute 'make_one_shot_iterator'

Can someone help me understand this error and how to fix it?

Broken shield badge

Had the same issue, I had to change the /github/workflow/ with /github/actions/workflow/ and add the explicit .yml extension of my action to get it working.

can't pickle SwigPyObject objects

I wish to use bpnn for nonperiodic (molecule) system.
The following error is returned by the model=potential_model(params) line:

File "E:\anaconda3\envs\p37env\lib\site-packages\yaml\representer.py", line 317, in represent_object
reduce = data.reduce_ex(2)

TypeError: can't pickle SwigPyObject objects

Thank you in advance for a comment in this issue.

TF>=2.10

Recent TensorFlow versions seem to break some important parts of PiNN.
I still need some time to pinpoint the problem, but according to this preliminary test:
The 2.10 version seem to break the jacobian calculation used in BPNN;
and the 2.11 version breaks basic derivative calcualtions used for potential models.
For now, I'll just mark those as incompatible in README, will update when I know more.

Migrating to TF2

Dear developers,

It's generally favorable to migrate to TF2, I'm aware of the following advantages

A cleaned up API (eager execution, removal of sessions, etc).
Built in support for using TensorBoard in Juptyer notebooks.
Possibly improved performance.

After some further fixes (mostly cleaning of naming) and upgrading
the current code base to TF1.15 (last 1.X) version, I'll try migrating
the code to TF2.

I'll not likely start immediately, but welcome comments and suggestions.

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