tf.keras.layers.Subtract
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Layer that subtracts two inputs.
tf.keras.layers.Subtract(
**kwargs
)
It takes as input a list of tensors of size 2,
both of the same shape, and returns a single tensor, (inputs[0] - inputs[1]),
also of the same shape.
Examples:
import keras
input1 = keras.layers.Input(shape=(16,))
x1 = keras.layers.Dense(8, activation='relu')(input1)
input2 = keras.layers.Input(shape=(32,))
x2 = keras.layers.Dense(8, activation='relu')(input2)
# Equivalent to subtracted = keras.layers.subtract([x1, x2])
subtracted = keras.layers.Subtract()([x1, x2])
out = keras.layers.Dense(4)(subtracted)
model = keras.models.Model(inputs=[input1, input2], outputs=out)
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.keras.layers.Subtract\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 2 version](/api_docs/python/tf/keras/layers/Subtract) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/keras/layers/merge.py#L253-L288) |\n\nLayer that subtracts two inputs.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.keras.layers.Subtract`](/api_docs/python/tf/keras/layers/Subtract), \\`tf.compat.v2.keras.layers.Subtract\\`\n\n\u003cbr /\u003e\n\n tf.keras.layers.Subtract(\n **kwargs\n )\n\nIt takes as input a list of tensors of size 2,\nboth of the same shape, and returns a single tensor, (inputs\\[0\\] - inputs\\[1\\]),\nalso of the same shape.\n\n#### Examples:\n\n import keras\n\n input1 = keras.layers.Input(shape=(16,))\n x1 = keras.layers.Dense(8, activation='relu')(input1)\n input2 = keras.layers.Input(shape=(32,))\n x2 = keras.layers.Dense(8, activation='relu')(input2)\n # Equivalent to subtracted = keras.layers.subtract([x1, x2])\n subtracted = keras.layers.Subtract()([x1, x2])\n\n out = keras.layers.Dense(4)(subtracted)\n model = keras.models.Model(inputs=[input1, input2], outputs=out)"]]