eb89648ac93c8b8503a1c1059707caad8ec71f78,keras/applications/resnet.py,,block3,#Any#Any#Any#Any#Any#Any#Any#,360

Before Change

      use_bias=False,
      name=name + "_2_conv")(x)
  x_shape = backend.int_shape(x)[1:-1]
  x = layers.Reshape(x_shape + (groups, c, c))(x)
  x = layers.Lambda(
      lambda x: sum(x[:, :, :, :, i] for i in range(c)),
      name=name + "_2_reduce")(x)
  x = layers.Reshape(x_shape + (filters,))(x)

After Change

      use_bias=False,
      name=name + "_2_conv")(x)
  x_shape = backend.shape(x)[:-1]
  x = backend.reshape(x, backend.concatenate([x_shape, (groups, c, c)]))
  x = layers.Lambda(
      lambda x: sum(x[:, :, :, :, i] for i in range(c)),
      name=name + "_2_reduce")(x)

Instances