graph_def.py

>>> import tensorflow as tf
>>> a = tf.Variable(tf.zeros([784, 10], name='a')
>>> print str(tf.get_default_graph().as_graph_def())
node {
  name: "a"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 784
          }
          dim {
            size: 10
          }
        }
        float_val: 0.0
      }
    }
  }
}
node {
  name: "Variable"
  op: "Variable"
  attr {
    key: "container"
    value {
      s: ""
    }
  }
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "shape"
    value {
      shape {
        dim {
          size: 784
        }
        dim {
          size: 10
        }
      }
    }
  }
  attr {
    key: "shared_name"
    value {
      s: ""
    }
  }
}
node {
  name: "Variable/Assign"
  op: "Assign"
  input: "Variable"
  input: "a"
  attr {
    key: "T"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "use_locking"
    value {
      b: true
    }
  }
  attr {
    key: "validate_shape"
    value {
      b: true
    }
  }
}
node {
  name: "Variable/read"
  op: "Identity"
  input: "Variable"
  attr {
    key: "T"
    value {
      type: DT_FLOAT
    }
  }
}

# node {
#   name: "a"
#   op: "Const"
#   attr {
#     key: "dtype"
#     value {
#       type: DT_FLOAT
#     }
#   }
#   attr {
#     key: "value"
#     value {
#       tensor {
#         dtype: DT_FLOAT
#         tensor_shape {
#           dim {
#             size: 784
#           }
#           dim {
#             size: 10
#           }
#         }
#         float_val: 0.0
#       }
#     }
#   }
# }
# node {
#   name: "Variable"
#   op: "Variable"
#   ...
# }
# node {
#   name: "Variable/Assign"
#   op: "Assign"
#   input: "Variable"
#   input: "a"
#   ...
# }