scripts/tf_cnn_benchmarks/models/resnet_model.py [60:71]:
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  with tf.variable_scope(name):
    if depth == in_size:
      if stride == 1:
        shortcut = input_layer
      else:
        shortcut = cnn.apool(
            1, 1, stride, stride, input_layer=input_layer,
            num_channels_in=in_size)
        mlperf.logger.log_projection(input_tensor=input_layer,
                                     output_tensor=shortcut)
    else:
      shortcut = cnn.conv(
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scripts/tf_cnn_benchmarks/models/resnet_model.py [165:176]:
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  with tf.variable_scope(name):
    if depth == in_size:
      if stride == 1:
        shortcut = input_layer
      else:
        shortcut = cnn.apool(
            1, 1, stride, stride, input_layer=input_layer,
            num_channels_in=in_size)
        mlperf.logger.log_projection(input_tensor=input_layer,
                                     output_tensor=shortcut)
    else:
      shortcut = cnn.conv(
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