class_docstr: Efficient linear layer for one-hot input.
  
  This is a link that wraps the :func:`~chainer.functions.embed_id` function.
  This link holds the ID (word) embedding matrix ``W`` as a parameter.
  
  Args:
      in_size (int): Number of different identifiers (a.k.a. vocabulary
          size).
      out_size (int): Size of embedding vector.
      initialW (:ref:`initializer <initializer>`): Initializer to
          initialize the weight. When it is :class:`numpy.ndarray`,
          its ``ndim`` should be 2.
      ignore_label (int or None): If ``ignore_label`` is an int value,
          ``i``-th row of return value is filled with ``0``.
  
  .. seealso:: :func:`~chainer.functions.embed_id`
  
  Attributes:
      W (~chainer.Variable): Embedding parameter matrix.
  
  .. admonition:: Example
  
      >>> W = np.array([[0, 0, 0],
      ...               [1, 1, 1],
      ...               [2, 2, 2]]).astype(np.float32)
      >>> W
      array([[0., 0., 0.],
             [1., 1., 1.],
             [2., 2., 2.]], dtype=float32)
      >>> l = L.EmbedID(W.shape[0], W.shape[1], initialW=W)
      >>> x = np.array([2, 1]).astype(np.int32)
      >>> x
      array([2, 1], dtype=int32)
      >>> y = l(x)
      >>> y.array
      array([[2., 2., 2.],
             [1., 1., 1.]], dtype=float32)
docstr: Extracts the word embedding of given IDs.
  
  Args:
      x (~chainer.Variable): Batch vectors of IDs.
  
  Returns:
      ~chainer.Variable: Batch of corresponding embeddings.
docstr_tok: ["Extracts","the","word","embedding","of","given","IDs",".","Args",":","x","(","~chainer.Variable",")",":","Batch","vectors","of","IDs",".","Returns",":","~chainer.Variable",":","Batch","of","corresponding","embeddings","."]
code: def forward(self, x):
      """Extracts the word embedding of given IDs.
  
      Args:
          x (~chainer.Variable): Batch vectors of IDs.
  
      Returns:
          ~chainer.Variable: Batch of corresponding embeddings.
  
      """
      return embed_id.embed_id(
          x, self.W, ignore_label=self.ignore_label
      )
  
file_path: chainer/chainer/links/connection/embed_id.py
imports: from chainer.functions.connection import embed_id
  from chainer.initializers import normal
  from chainer import link
  from chainer import variable
label_desc: Use image node_id 3 for calling the EmbedID obj's underlying member method code with example usage: obj.forward(x) and returns: embed_id