olivettigroup / materials-synthesis-generative-models Goto Github PK

Hi,
You reference the vocab.txt file here for example but I didn't understand which one is the default- is it a default ELMO vocabulary or one that you generated from mat-sci papers? I didn't see any at the links you provided.

Thanks for making these resources available!

Hi,

Thanks for your interesting work. I am wondering if the embedding is checked for the organic materials, such as different linkers.

Thanks!

Hi,
many thanks for open-sourcing code and models, which we want to use to classify a large corpus of papers on synthesis.
Could someone could help me out real quick with the following issue? I run

p = paragraph_classifier.ParagraphClassifier()
p.load("/home/ubuntu/scratch/models/paragraph_classifier.model")

where the path points to the pre-trained model in https://figshare.com/s/1a07d18ad20008ddd562.

I get the following error message (below). Could the issue be different code version or am I doing something wrong?

Many thanks,

Libraries

Keras==2.4.3
Keras-Preprocessing==1.1.2
tensorflow==2.3.1
tensorflow-cpu==2.3.1
tensorflow-estimator==2.3.0
Python 3.8.6

Traceback

ValueError Traceback (most recent call last)
in
----> 1 p.load("/home/ubuntu/scratch/models/paragraph_classifier.model")

~/git/materials-synthesis-generative-models/models/paragraph_classifier.py in load(self, filename)
105 def load(self, filename='bin/paragraph_classifier.model'):
106 self.model = load_model(filename)
--> 107 self.fast_predict = K.function(
108 [self.model.inputs] + [K.learning_phase()],
109 [self.model.layers[-1].output]

~/.virtualenvs/deepmd/lib/python3.8/site-packages/tensorflow/python/keras/backend.py in function(inputs, outputs, updates, name, **kwargs)
3934 from tensorflow.python.keras import models # pylint: disable=g-import-not-at-top
3935 from tensorflow.python.keras.utils import tf_utils # pylint: disable=g-import-not-at-top
-> 3936 model = models.Model(inputs=inputs, outputs=outputs)
3937
3938 wrap_outputs = isinstance(outputs, list) and len(outputs) == 1

~/.virtualenvs/deepmd/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py in new(cls, *args, **kwargs)
240 # Functional model
241 from tensorflow.python.keras.engine import functional # pylint: disable=g-import-not-at-top
--> 242 return functional.Functional(*args, **kwargs)
243 else:
244 return super(Model, cls).new(cls, *args, **kwargs)

~/.virtualenvs/deepmd/lib/python3.8/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
455 self._self_setattr_tracking = False # pylint: disable=protected-access
456 try:
--> 457 result = method(self, *args, **kwargs)
458 finally:
459 self._self_setattr_tracking = previous_value # pylint: disable=protected-access

~/.virtualenvs/deepmd/lib/python3.8/site-packages/tensorflow/python/keras/engine/functional.py in init(self, inputs, outputs, name, trainable)
113 # 'arguments during initialization. Got an unexpected argument:')
114 super(Functional, self).init(name=name, trainable=trainable)
--> 115 self._init_graph_network(inputs, outputs)
116
117 @trackable.no_automatic_dependency_tracking

~/.virtualenvs/deepmd/lib/python3.8/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
455 self._self_setattr_tracking = False # pylint: disable=protected-access
456 try:
--> 457 result = method(self, *args, **kwargs)
458 finally:
459 self._self_setattr_tracking = previous_value # pylint: disable=protected-access

~/.virtualenvs/deepmd/lib/python3.8/site-packages/tensorflow/python/keras/engine/functional.py in _init_graph_network(self, inputs, outputs)
142 base_layer_utils.create_keras_history(self._nested_outputs)
143
--> 144 self._validate_graph_inputs_and_outputs()
145
146 # A Network does not create weights of its own, thus it is already

~/.virtualenvs/deepmd/lib/python3.8/site-packages/tensorflow/python/keras/engine/functional.py in _validate_graph_inputs_and_outputs(self)
634 if not hasattr(x, '_keras_history'):
635 cls_name = self.class.name
--> 636 raise ValueError('Input tensors to a ' + cls_name + ' ' +
637 'must come from tf.keras.Input. '
638 'Received: ' + str(x) +

ValueError: Input tensors to a Functional must come from tf.keras.Input. Received: 0 (missing previous layer metadata).

Hi,
I am trying to use the pre-trained Elmo embeddings for materials. However, I could not find the vocab file on figshare.
Request you to please share. I read that default vocab file works fine. In that case, where is this file located?

Many thanks in advance.

Hello, Is there any plan to release the article database for non-profit/academic research work?