Bug fix: Models with shared layers shouldn't be considered Sequential like #8025
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farizrahman4u
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fchollet
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Sep 30, 2017
| for layer in model.layers: | ||
| flag = False | ||
| for node in layer.inbound_nodes: | ||
| if node in nodes: |
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Not necessarily. A layer might be shared between 2 models and hence have more than one inbound node. But we are looking for layers which are being shared within the same model. The inbound nodes should be part of the graph of the model for which we are printing the summary.
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dense = Dense(10)
a = Input((10,))
b = dense(a)
model1 = Model(a, b)
a2 = Input((10,))
b2 = dense(a2)
model2 = Model(a2, b2)
model1.summary()
# Here dense layer has 2 inbound nodes,
#but the second node is not part of model1.
# So should be considered sequential like| if (len(v) > 1) or (len(v) == 1 and len(v[0].inbound_layers) > 1): | ||
| # if the model has multiple nodes or if the nodes have multiple inbound_layers | ||
| # the model is no longer sequential | ||
| sequential_like = False | ||
| break | ||
| nodes += v | ||
| if sequential_like: | ||
| # search for shared layers |
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I don't get the criteria you use for shared layers. A comment here would help
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A layer is shared in a model if it has 2 or more inbound nodes and those inbound nodes are part of the graph.
keras/utils/layer_utils.py
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| flag = True | ||
| if not sequential_like: | ||
| break | ||
| del nodes |
fchollet
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Oct 2, 2017
ozabluda
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Oct 2, 2017
… like (keras-team#8025) * models with shared layers are not sequential * pep8 * remove del statement
dschwertfeger
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Oct 8, 2017
…-outputs * master: (68 commits) Change default value of shuffle parameter of Sequential.fit_generator() from True to False. (keras-team#8075) Fix off-by-one bug in predict/evaluate progress bar (keras-team#8071) Revert "Faster sequence" (keras-team#8060) Support NCHW for conv2d. (keras-team#8021) Change compute_accuracy() argument order and names (keras-team#8049) Replace literal constant 10 with variable num_classes in example/ (keras-team#8041) Faster sequence (keras-team#8039) Improve RNN docs. Enable accuracy reporting during training in examples/mnist_siamese_graph.py (keras-team#7997) Bug fix: Models with shared layers shouldn't be considered Sequential like (keras-team#8025) Add 'subtract' merge layer documentation (keras-team#8038) Update inference in seq2seq script to be more efficient Remove lstm_benchmark from examples/README.md (keras-team#8024) Add shuffle to the Model API (keras-team#8023) Add seq2seq example script. fix travis failure (keras-team#8014) Improve TF backend's Switch function (keras-team#7958) Added support for dynamic noise_shape in Dropout (keras-team#7999) Make on_epoch_end optional (keras-team#8007) Incremental tests speed ups. ...
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As of now, the following model is being considered as a "Sequential-like":