old_contents: # Copyright (c) 2017 Sony Corporation. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import pytest
  import numpy as np
  import nnabla as nn
  import nnabla.functions as F
  from nbla_test_utils import list_context
  
  ctxs = list_context('EpsilonInsensitiveLoss')
  
  
  def ref_epsilon_insensitive_loss_forward(x0, x1, epsilon):
      y = np.zeros_like(x0)
      abs_diff = np.abs(x0 - x1)
      idx = np.where(abs_diff > epsilon)
      y[idx] = abs_diff[idx] - epsilon
      return y
  
  
  @pytest.mark.parametrize("ctx, func_name", ctxs)
  @pytest.mark.parametrize("seed", [313])
  @pytest.mark.parametrize("epsilon", [0.001, 1])
  def test_epsilon_insensitive_loss_forward_backward(seed, ctx, func_name, epsilon):
      pytest.skip('Temporarily skipped.')
      from nbla_test_utils import function_tester
      rng = np.random.RandomState(seed)
      inputs = [rng.randn(2, 3, 4).astype(np.float32) * 2 for _ in range(2)]
      function_tester(rng, F.epsilon_insensitive_loss,
                      ref_epsilon_insensitive_loss_forward, inputs,
                      func_args=[epsilon],
                      atol_b=1e-2, atol_f=0.5, ctx=ctx, func_name=func_name)
  
new_contents: # Copyright (c) 2017 Sony Corporation. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import pytest
  import numpy as np
  import nnabla as nn
  import nnabla.functions as F
  from nbla_test_utils import list_context
  
  ctxs = list_context('EpsilonInsensitiveLoss')
  
  
  def ref_epsilon_insensitive_loss_forward(x0, x1, epsilon):
      y = np.zeros_like(x0)
      abs_diff = np.abs(x0 - x1)
      idx = np.where(abs_diff > epsilon)
      y[idx] = abs_diff[idx] - epsilon
      return y
  
  
  @pytest.mark.parametrize("ctx, func_name", ctxs)
  @pytest.mark.parametrize("seed", [313])
  @pytest.mark.parametrize("epsilon", [0.001, 1])
  def test_epsilon_insensitive_loss_forward_backward(seed, ctx, func_name, epsilon):
      pytest.skip('Temporarily skipped.')
      from nbla_test_utils import function_tester
      rng = np.random.RandomState(seed)
      inputs = [rng.randn(2, 3, 4).astype(np.float32) * 2 for _ in range(2)]
      function_tester(rng, F.epsilon_insensitive_loss,
                      ref_epsilon_insensitive_loss_forward, inputs,
                      func_args=[epsilon],
                      atol_b=1e-2, ctx=ctx, func_name=func_name)
  
subject: Revert test parameter change. (but still skipping)