Error: OOM when allocating tensor with shape
OOM stands for Out Of Memory.  That means that your GPU has run out of space, presumably because you've allocated other tensors which are too large.  You can fix this by making your model smaller or reducing your batch size.  By the looks of it, you're feeding in a large image (800x1280) you may want to consider downsampling.
i am facing issue with my inception model during the performance testing with Apache JMeter.

Error: OOM when allocating tensor with shape[800,1280,3] and type
  float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator
  GPU_0_bfc      [[Node: Cast = CastDstT=DT_FLOAT, SrcT=DT_UINT8,
  _device="/job:localhost/replica:0/task:0/device:GPU:0"]]
  Hint: If you want to see a list of allocated tensors when OOM happens,
  add report_tensor_allocations_upon_oom to RunOptions for current
  allocation info.