value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 1
      }
    }
  }
}
node {
  name: "Const_1"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }

    Tensor* cpu_tensor, StatusCallback done) {
  DataType dtype = EncodePrimitiveTypeAsDataType(shape_.element_type()).value();
  TensorShape tensor_shape;
  Status status = XLAShapeToTensorShape(shape_, &tensor_shape);
  if (!status.ok()) {
    done(status);
    return;
  }

  *cpu_tensor = Tensor(dtype, tensor_shape);

  status = stream_->Memcpy(cpu_tensor->data(), device_memory_base_,
                           device_memory_base_.size());

  name: "predicate"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }
  experimental_debug_info {
  }
}
node {
  name: "Case"
  op: "Case"
  input: "predicate"
  attr {
    key: "Tin"
    value {

      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: -1
      }
    }
  }
}
node {
  name: "while/loop_counter"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }

node {
  name: "Constant"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }
}
node {
  name: "_tf.foo"
  op: "foo"
  input: "Constant"
}
library {
  function {
    signature {
      name: "foo"

    value {
      tensor {
        dtype: DT_INT32
        tensor_shape { dim { size: 1 } }
        int_val: 1
      }
    }
  }
  attr { key  : "dtype" value { type: DT_INT32 } }
}
node {
  name  : "y_const"
  op    : "Const"
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape { dim { size: 1 } }
        int_val: 2
      }
    }
  }

node {
  name: "Const"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }
}
node {
  name: "while/Enter"
  op: "Enter"
  input: "Const"
  attr {
    key: "T"
    value {
      type: DT_INT32
    }
  }

    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }
}
node {
  name: "Case/input_0"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
        }
        float_val: 1
      }
    }

#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_UTILS_CONVERT_TYPE_H_

#include "mlir/IR/Builders.h"  // from @llvm-project
#include "mlir/IR/Types.h"  // from @llvm-project
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/framework/types.pb.h"

namespace tensorflow {

using tsl::StatusOr;

// Converts the TensorFlow DataType 'dtype' into an MLIR (scalar) type.

      tensor {
        dtype: DT_INT64
        tensor_shape {
        }
        int64_val: 5
      }
    }
  }
}
node {
  name: "drop_remainder"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_BOOL
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_BOOL
        tensor_shape {
        }
        bool_val: false
      }