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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def compute_v(self, memory_antecedent):
 """Compute value Tensor v. Args: memory_antecedent: a Tensor with dimensions {memory_input_dim} + other_dims Returns: a Tensor with dimensions memory_heads_dims + {value_dim} + other_dims """

    if self.shared_kv:
      raise ValueError("compute_v cannot be called with shared_kv")
    ret = mtf.einsum(
        [memory_antecedent, self.wv], reduced_dims=[self.memory_input_dim])
    if self.combine_dims:
      ret = mtf.replace_dimensions(ret, ret.shape.dims[-1], self.v_dims)
    return ret