code: def compute_distance_matrix_unit_l2(a, b, eps=1e-6):
      """
      computes pairwise Euclidean distance and return a N x N matrix
      """
  
      dmat = torch.matmul(a, torch.transpose(b, 0, 1))
      dmat = ((1.0 - dmat + eps) * 2.0).pow(0.5)
      return dmat
  
imports: import torch
  import torch.nn
  from pytorch_metric_learning.utils import common_functions
  from pytorch_metric_learning.utils import loss_and_miner_utils
  import unittest
  from pytorch_metric_learning.losses import DynamicSoftMarginLoss
  from ..None import TEST_DEVICE, TEST_DTYPES
  from ..zzz_testing_utils.testing_utils import angle_to_coord
label_desc: Use image node_id 1 for calling a global function with example usage: compute_distance_matrix_unit_l2(a, b, eps) and returns: dmat