clustering_ops.py 文件源码

def _compute_euclidean_distance(cls, inputs, clusters):
    """Computes Euclidean distance between each input and each cluster center.

    Args:
      inputs: list of input Tensors.
      clusters: cluster Tensor.

    Returns:
      list of Tensors, where each element corresponds to each element in inputs.
      The value is the distance of each row to all the cluster centers.
    """
    output = []
    for inp in inputs:
      with ops.colocate_with(inp):
        # Computes Euclidean distance. Note the first and third terms are
        # broadcast additions.
        squared_distance = (math_ops.reduce_sum(
            math_ops.square(inp), 1, keep_dims=True) - 2 * math_ops.matmul(
                inp, clusters, transpose_b=True) + array_ops.transpose(
                    math_ops.reduce_sum(
                        math_ops.square(clusters), 1, keep_dims=True)))
        output.append(squared_distance)

    return output