Function euclideanNorm

  • euclideanNorm(x, axis?, keepDims?): Tensor

  • Computes the Euclidean norm of scalar, vectors, and matrices.

    const x = tf.tensor1d([1, 2, 3, 4]);

    x.euclideanNorm().print();  // or tf.euclideanNorm(x)

    Parameters

    • x: Tensor<Rank> | TensorLike

      The input array.

    • Optional axis: number | number[]

      Optional. If axis is null (the default), the input is considered a vector and a single vector norm is computed over the entire set of values in the Tensor, i.e. euclideanNorm(x) is equivalent to euclideanNorm(x.reshape([-1])). If axis is an integer, the input is considered a batch of vectors, and axis determines the axis in x over which to compute vector norms. If axis is a 2-tuple of integer it is considered a batch of matrices and axis determines the axes in NDArray over which to compute a matrix norm.

    • Optional keepDims: boolean

      Optional. If true, the norm has the same dimensionality as the input.

    Returns Tensor

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