class_docstr: Get an embedding from the instrument one-hot.
code: def build(self, cond_shape):
      # pylint: disable=unused-argument
      self.embedding = nn.get_embedding(
          vocab_size=self.vocab_size, n_dims=self.n_dims
      )
  
imports: import ddsp
  from ddsp import spectral_ops
  from ddsp.training import nn
  import gin
  import tensorflow.compat.v2
label_desc: Use image node_id 2 for calling the OneHotEncoder obj's underlying member method code with example usage: obj.build(cond_shape) without return types