Converted Tensorrt model has different output shape from Tensorflow model

AI & Data Science Deep Learning (Training & Inference) TensorRT
1

I have a tensorflow model and converted to tensorrt model.
Tensorflow model’s uff conversion shown below. Input is image and output is Openpose/concat_stage7

NOTE: UFF has been tested with TensorFlow 1.12.0. Other versions are not guaranteed to work
UFF Version 0.6.3
=== Automatically deduced input nodes ===
[name: "image"
op: "Placeholder"
attr {
  key: "dtype"
  value {
    type: DT_FLOAT
  }
}
attr {
  key: "shape"
  value {
    shape {
      dim {
        size: -1
      }
      dim {
        size: -1
      }
      dim {
        size: -1
      }
      dim {
        size: 3
      }
    }
  }
}
]
=========================================

=== Automatically deduced output nodes ===
[name: "Openpose/concat_stage7"
op: "ConcatV2"
input: "Mconv7_stage6_L2/BiasAdd"
input: "Mconv7_stage6_L1/BiasAdd"
input: "Openpose/concat_stage7/axis"
attr {
  key: "N"
  value {
    i: 2
  }
}
attr {
  key: "T"
  value {
    type: DT_FLOAT
  }
}
attr {
  key: "Tidx"
  value {
    type: DT_INT32
  }
}
]
==========================================

Using output node Openpose/concat_stage7
Converting to UFF graph
No. nodes: 463
UFF Output written to cmu/cmu_openpose.uff

Tensorflow model output shape is
self.tensor_output = self.graph.get_tensor_by_name(‘TfPoseEstimator/Openpose/concat_stage7:0’)
(?, ?, ?, 57)

When i run tensorrt, output dimension is (217500,)?
How to have same dimension as Tensorflow model?