Tensorflow.js tf.input() Function
Last Updated :
21 Jul, 2021
The models in deep learning are collections of connected Layers which can be trained, evaluate, and can be used to predict something. To perform this operation you need to instantiate an input to the models. In this post, We are going to know about how the input factory function works.
The tf.input() function is used when model created using tf.model() function.
Syntax:
tf.input(Args)
Parameters: The Args object contains the following props.
- Shape: It represents expected input will be batches of 32-dimensional vectors.
- batchShape: It represents shape tuple including batch size.
- name: It represents the name for the layer.
- dtype: It is used to denote the type of input.
- sparse: A boolean value represents the placeholder created is sparse.
Returns: It returns the tf.SymbolicTensor.
Example 1: In this example, we are going to use the default parameter shape.
Javascript
const tf = require( "@tensorflow/tfjs" )
const inp = tf.input({ shape: [64] });
const op = tf.layers.dense({ units: 8, activation: 'softmax' }).apply(inp);
const model = tf.model({ inputs: inp, outputs: op });
model.predict(tf.ones([2, 64])).print();
|
Output:
Tensor
[[0.0285837, 0.1409771, 0.1021329, 0.0912676, 0.2361873, 0.0262359,
0.2991393, 0.0754762],
[0.0285837, 0.1409771, 0.1021329, 0.0912676, 0.2361873, 0.0262359,
0.2991393, 0.0754762]]
Example 2: In this example, we are going to use all parameters shape, name, type, and sparse.
Javascript
const tf = require( "@tensorflow/tfjs" )
const inp = tf.input({ shape: [16] }, { name: 'abc' },
{ dtype: 'float32' }, { sparse: false });
const op = tf.layers.dense({ units: 2, activation: 'softmax' }).apply(inp);
const model = tf.model({ inputs: inp, outputs: op });
model.summary();
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Output:
Layer (type) Output shape Param #
=================================================================
input8 (InputLayer) [null,16] 0
_________________________________________________________________
dense_Dense8 (Dense) [null,2] 34
=================================================================
Total params: 34
Trainable params: 34
Non-trainable params: 0
_________________________________________________________________
References: https://js.tensorflow.org/api/latest/#input
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