docstr: Embeds the inputs along the last dimension.
  
  Args:
    indices: input data, all dimensions are considered batch dimensions.
  
  Returns:
    Output which is embedded input data.  The output shape follows the input,
    with an additional `features` dimension appended.
docstr_tok: ["Embeds","the","inputs","along","the","last","dimension",".","Args",":","indices",":","input","data",",","all","dimensions","are","considered","batch","dimensions",".","Returns",":","Output","which","is","embedded","input","data",".","The","output","shape","follows","the","input",",","with","an","additional","`","features","`","dimension","appended","."]
code: def lookup(self, indices):
      """Embeds the inputs along the last dimension.
  
      Args:
        indices: input data, all dimensions are considered batch dimensions.
  
      Returns:
        Output which is embedded input data.  The output shape follows the input,
        with an additional `features` dimension appended.
      """
      if indices.dtype not in [
          jnp.int32,
          jnp.int64,
          jnp.uint32,
          jnp.uint64,
      ]:
          raise ValueError(
              "Input type must be an integer or unsigned integer."
          )
      return self.table[indices]
  
file_path: flax/flax/core/nn/linear.py
imports: from collections.abc import Iterable
  import jax.numpy
  import numpy
  from jax import lax
  from flax import struct
  from flax.core import Scope
  from flax.linen import initializers
label_desc: Use image node_id 1 for calling the Embedding obj's underlying member method code with example usage: obj.lookup(indices) and returns: self