I am trying to create a constant variable inside a keras model. What I was doing till now is to pass it as Input. But it is always a constant so I want it as a constant.(The input is [1,2,3...50] for each example => so I use np.tile(np.array(range(50)),(len(X_input))) to reproduce it for each example)
So for now I had:
constant_input = Input(shape=(50,), dtype='int32', name="constant_input")
Which gives a tensor: Tensor("constant_input", shape(?,50), dtype=int32)
Now trying to do it as a constant:
np_constant = np.array(list(range(50))).reshape(1, 50)
tf_constant = K.constant(np_constant)
tensor_constant = Input(tensor=tf_constant, shape=(50,), dtype='int32', name="constant_input")
which gives a tensor: Tensor("constant_input", shape(50,1),dtype=float32)
But What I want is the constant to be scaled in each batch, meaning that the shape of the tensor should be (?, 50), the same as the way of using Input.
Is it possible to do that?
You cannot have a constant with variable size. A constant always has the same value. What you can do is have the (1, 50) constant and then tile it within TensorFlow with K.tile. Also better use np.arange instead of np.array(list(range(50)). Something like:
from keras.layers.core import Lambda
import keras.backend as K
def operateWithConstant(input_batch):
tf_constant = K.constant(np.arange(50).reshape((1, 50)))
batch_size = K.shape(input_batch)[0]
tiled_constant = K.tile(tf_constant, (batch_size, 1))
# Do some operation with tiled_constant and input_batch
result = ...
return result
input_batch = Input(...)
input_operated = Lambda(operateWithConstant)(input_batch)
# continue...
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