Cannot find multigride architecture

Hi,@rishizek: Thanks for your implementation of deeplabV3, but I cannot find the multigride architecture as you mentioned in the Evaluation of README file: “repo | MG(1,2,4)+ASPP(6,12,18)+Image Pooling | 16 | 76.42%”.Can you tell me where did you put the code of this multigride architecture? blocks = [ resnet_v2_block('block1', base_depth=64, num_units=3, stride=2), resnet_v2_block('block2', base_depth=128, num_units=4, stride=2), resnet_v2_block('block3', base_depth=256, num_units=23, stride=2), resnet_v2_block('block4', base_depth=512, num_units=3, stride=1), ]

[rishizek]

Hi @FlyingIce1 , thank you for your interest in the repo.

It is complex but the multigrid architecture is implemented in slim library. The key parameter is output_stride, which you can find document explanation here and here. The default output stride of ResNet is 32, as you may know from ResNet and Deeplab papers. When you set output_stride = 16, the slim module automatically sets MG(1,2,4). More concretely, if you set ouput_stirde = 16, after current_stride=16 here, the rate parameter (which is also know as atrous convolution rate parameter) here will be multiplied instead of stride afterword. And this creates MG(1,2,4). The resnet_v2_block() functions you mentioned will eventually return resnet_utils.Block() class here if you read code carefully, so it is OK to overwrite rate parameter later on.

I hope this answers your question.

[northeastsquare]

@luke-evans-liu @a7b23 @rishizek no mater output_stride=16 or 8, the atrous rate is always (1,1,1), reason as follows, so where am I wrong? because https://github.com/tensorflow/tensorflow/blob/r1.8/tensorflow/contrib/slim/python/slim/nets/resnet_v2.py#L208 output_stride=output_stride/4, everytime https://github.com/tensorflow/tensorflow/blob/r1.8/tensorflow/contrib/slim/python/slim/nets/resnet_utils.py#L216 current_stride *= unit.get(‘stride’, 1), current_stride=1 alwalys since unit.get(‘stride’, 1) =1, and output_stride=4 or 2 (as output_stride/4, as upper) since https://github.com/tensorflow/tensorflow/blob/r1.8/tensorflow/contrib/slim/python/slim/nets/resnet_v2.py#L276 bock4 stride=1. this line https://github.com/tensorflow/tensorflow/blob/23c218785eac5bfe737eec4f8081fd0ef8e0684d/tensorflow/contrib/slim/python/slim/nets/resnet_utils.py#L211 will never be executed.

so can I change the code mannually, https://github.com/tensorflow/tensorflow/blob/23c218785eac5bfe737eec4f8081fd0ef8e0684d/tensorflow/contrib/slim/python/slim/nets/resnet_utils.py#L210 to make rate=[1,2,4] ? that is to say, change the code as following: ` for ib, block in enumerate(blocks): with variable_scope.variable_scope(block.scope, ‘block’, [net]) as sc: for i, unit in enumerate(block.args): if output_stride is not None and current_stride > output_stride: raise ValueError(‘The target output_stride cannot be reached.’)

    with variable_scope.variable_scope('unit_%d' % (i + 1), values=[net]):
      # If we have reached the target output_stride, then we need to employ
      # atrous convolution with stride=1 and multiply the atrous rate by the
      # current unit's stride for use in subsequent layers.
      print('ib:', ib) 
      if ib == 3:
        rate = pow(2, i)
        print("rate:", rate)
        net = block.unit_fn(net, rate=rate, **dict(unit, stride=1))
      elif output_stride is not None and current_stride == output_stride:
        net = block.unit_fn(net, rate=rate, **dict(unit, stride=1))
        rate *= unit.get('stride', 1)

      else:
        net = block.unit_fn(net, rate=1, **unit)
        current_stride *= unit.get('stride', 1)
  net = utils.collect_named_outputs(outputs_collections, sc.name, net)

`