}
}
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  input: "Const"
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    }
  }
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}
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    key: "T"
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      type: DT_FLOAT
    }
  }
  attr {
    key: "out_type"
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    }
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    key: "dilations"
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      list {
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    key: "explicit_paddings"
    value {
      list {
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  attr {
    key: "padding"
    value {
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node {
  name: "arg0"
  op: "_Arg"
  attr {
    key: "T"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "index"
    value {
      i: 0
    }
  }
}
node {
  name: "arg1"
  op: "_Arg"
  attr {
    key: "T"
    value {
      type: DT_RESOURCE
    }
  }
  attr {
    key: "_handle_dtypes"
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      type: DT_BOOL
    }
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  attr {
    key: "Tin"
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      list {
        type: DT_FLOAT
        type: DT_FLOAT
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  attr {
    key: "Tout"
    value {
      list {
        type: DT_FLOAT
      }
    }
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  input: "b"
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  attr {
    key: "Tin"
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        type: DT_FLOAT
        type: DT_FLOAT
        type: DT_FLOAT
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        type: DT_FLOAT

  input: "x"
  input: "m"
  input: "v"
  input: "beta"
  input: "gamma"
  device: "/device:CPU:0"
  attr {
    key: "T"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "scale_after_normalization"
    value {
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  attr {
    key: "variance_epsilon"
    value {
      f: 0.001
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  }
}
library {
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  attr {
    key: "frame_name"
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      s: "while_context"
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  }
  attr {
    key: "is_constant"
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    }
  }
  attr {
    key: "parallel_iterations"
    value {
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}
node {
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  op: "Merge"
  input: "Enter"
  input: "NextIteration"
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    key: "N"
    value {
      i: 2
    }
  }
  attr {

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    if (attr.type() == "int") {
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    } else if (attr.type() == "list(int)") {
      std::vector<int> v(attr.minimum());
      for (int i = 0; i < v.size(); ++i) v[i] = i;
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  if (attr.has_allowed_values()) {

node {
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    }
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    key: "Tout"
    value {
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      }
    }
  }
  attr {
    key: "_gradient_op_type"
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  attr {
    key: "config"
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  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
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        tensor_shape {
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        int_val: 3
      }
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  experimental_debug_info {
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}
node {
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  op: "Const"
  attr {
    key: "dtype"
    value {