gdb --args .build_debug/tools/caffe train --solver=examples/mnist/lenet_solver.prototxt

inline Dtype Layer<Dtype>::Forward(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top)

(gdb) p bottom
$30 = std::vector of length 2, capacity 2 = {0x4c24300, 0x4b12fd0}
(gdb) what bottom
type = const std::vector<caffe::Blob<float>*, std::allocator<caffe::Blob<float>*> > &
(gdb) what bottom[0]
type = std::vector<caffe::Blob<float>*, std::allocator<caffe::Blob<float>*> >::reference
(gdb) what bottom[0][0]
type = caffe::Blob<float>

(gdb) p bottom[0][0]
$42 = {
  data_ = {
    px = 0x4c23710,
    pn = {
      pi_ = 0x4c23740
    }
  },
  diff_ = {
    px = 0x4c23fc0,
    pn = {
      pi_ = 0x4c23ff0
    }
  },
  shape_data_ = {
    px = 0x4c23f00,
    pn = {
      pi_ = 0x4c23f30
    }
  },
  shape_ = std::vector of length 2, capacity 2 = {100, 10},
  count_ = 1000,
  capacity_ = 1000
}

(gdb) p bottom[0][0].data_
$43 = {
  px = 0x4c23710,
  pn = {
    pi_ = 0x4c23740
  }
}
(gdb) p bottom[0][0].data_.px[0]
$44 = {
  cpu_ptr_ = 0x474fef0,
  gpu_ptr_ = 0x0,
  size_ = 4000,
  head_ = caffe::SyncedMemory::HEAD_AT_CPU,
  own_cpu_data_ = true,
  cpu_malloc_use_cuda_ = false,
  own_gpu_data_ = false,
  gpu_device_ = -1
}