class_docstr: Choose a slice of input on the last axis given order,
  Suppose input x has two dimensions,
  output f(x) = x[:, slice_num:slice_num+1]
class_docstr_tok: ["Choose","a","slice","of","input","on","the","last","axis","given","order",",","Suppose","input","x","has","two","dimensions",",","output","f","(","x",")","=","x","[",":",",","slice_num",":","slice_num+1","]"]
code: def call(self, inputs):
      slice_num = self.slice_num
      axis = self.axis
      return tf.slice(
          inputs, [0] * axis + [slice_num], [-1] * axis + [1]
      )
  
imports: import numpy
  import tensorflow
  from deepchem.models import KerasModel, layers
  from deepchem.models.losses import SigmoidCrossEntropy
  from tensorflow.keras.layers import Input, Layer, Activation, Concatenate, Lambda
  import warnings
label_desc: Use image node_id 2 for calling the Slice obj's underlying member method code with example usage: obj.call(inputs) and returns: tf