I am new to keras, and got some problems understanding the keras.layers.Dot() layer.
I am trying to calculate a dot product of two vectors.
from keras.layers import Input, Dot
from keras.models import Model
import numpy as np
x1 = Input(shape=(4,))
x2 = Input(shape=(4,))
y1 = Dot(axes=1)([x1,x2])
model = Model(inputs=[x1, x2], outputs=y1)
a1 = np.arange(4)
a2=np.arange(4)
model.predict([a1,a2])
I expect the output to be 14=0+1^2+2^2+3^2. However, I got error message like below:
ValueError: Error when checking input: expected input_46 to have shape (4,) but got array with shape (1,)
I tried to run model.get_config(), and below is the corresponding information about the graph of the model. As you can see input_46 is x1, and input_47 is x2.
{'name': 'model_19',
'layers': [{'name': 'input_46',
'class_name': 'InputLayer',
'config': {'batch_input_shape': (None, 4),
'dtype': 'float32',
'sparse': False,
'name': 'input_46'},
'inbound_nodes': []},
{'name': 'input_47',
'class_name': 'InputLayer',
'config': {'batch_input_shape': (None, 4),
'dtype': 'float32',
'sparse': False,
'name': 'input_47'},
'inbound_nodes': []},
{'name': 'dot_20',
'class_name': 'Dot',
'config': {'name': 'dot_20',
'trainable': True,
'axes': 1,
'normalize': False},
'inbound_nodes': [[['input_46', 0, 0, {}], ['input_47', 0, 0, {}]]]}],
'input_layers': [['input_46', 0, 0], ['input_47', 0, 0]],
'output_layers': [['dot_20', 0, 0]]}
Is there anything I didn't do right? Thanks!
UPDATE
The following code worked:
x1 = Input(shape=(4,))
x2 = Input(shape=(4,))
y1 = Dot(axes=1)([x1,x2])
model = Model(inputs=[x1, x2], outputs=y1)
a1 = np.arange(4).reshape(1,4)
a2=np.arange(4).reshape(1,4)
model.predict([a1,a2])
or
from keras.layers import Input, Dot
from keras.models import Model
import numpy as np
x1 = Input(shape=(4,))
x2 = Input(shape=(4,))
y1 = Dot(axes=1)([x1,x2])
model = Model(inputs=[x1, x2], outputs=y1)
a1 = np.arange(4)
a2=np.arange(4)
model.predict([[a1],[a2]])
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