}
      }
    }
  }
}
node {
  name: "BoxPredictor_4/ClassPredictor/weights"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
            size: 1
          }
          dim {
            size: 1
          }

  mutex_lock ml(*variable->mu());
  OP_REQUIRES(
      context,
      !variable->is_initialized || variable->tensor()->dtype() == dtype_,
      errors::InvalidArgument(
          "Trying to assign variable with wrong dtype. Expected ",
          DataTypeString(variable->tensor()->dtype()), " got ",
          DataTypeString(dtype_)));
  variable->is_initialized = true;
  *variable->tensor() = value;
}

        dtype: DT_FLOAT
        tensor_shape {
          dim {
          }
        }
      }
    }
  }
}
node {
  name: "ParseExample/Const_1"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
          }
        }
      }

    %4:2 = tf_executor.island(%3#2) wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", value = dense<10> : tensor<i32>} : () -> tensor<i32> loc("while/Less/y")
    %5:2 = tf_executor.island(%3#2) wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_BOOL", value = dense<true> : tensor<i1>} : () -> tensor<i1> loc("while/Less")

    %0:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<i32>} : () -> (tensor<i32>) loc("^foo")
    // CHECK: name: "fo.o"
    %1:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<1> : tensor<i32>} : () -> (tensor<i32>) loc("fo{o")
    // CHECK: name: "foo"

        attr {
          name: "T"
          type: "type"
          allowed_values {
            list {
              type: DT_HALF
              type: DT_FLOAT
              type: DT_DOUBLE
              type: DT_UINT8
              type: DT_INT8
              type: DT_INT16
              type: DT_INT32
              type: DT_INT64
              type: DT_COMPLEX64
              type: DT_COMPLEX128
              type: DT_STRING

                                           DataType dtype, TensorShape shape,
                                           const char* raw_device_name,
                                           ImmediateTensorHandlePtr* handle);

// Executes an AssignVariableOp using `ctx`, assigning the variable associated
// with `variable_handle` with `value`. `dtype` must be the datatype of the

                                     const char* attr_name,
                                     const TF_DataType type,
                                     TF_Status* status) {
  tensorflow::DataType dtype = static_cast<tensorflow::DataType>(type);
  tensorflow::AddTypeConstraint(kernel_builder, attr_name, dtype, status);
}

void TF_KernelBuilder_HostMemory(TF_KernelBuilder* kernel_builder,

TensorSpec::TensorSpec(PartialTensorShape shape, DataType dtype)
    : shape_(std::move(shape)), dtype_(dtype) {}

TensorSpec::TensorSpec(const TensorSpecProto& proto)
    : shape_(proto.shape()), dtype_(proto.dtype()) {}

const PartialTensorShape& TensorSpec::shape() const { return shape_; }

DataType TensorSpec::dtype() const { return dtype_; }

// Restores a single non-partioned tensorhandle of dtype `dtype`, using
// checkpoint at `prefix`, with a value stored in `checkpoint_key`.
Status SingleRestore(ImmediateExecutionContext* ctx, const std::string& prefix,
                     const std::string& checkpoint_key, DataType dtype,
                     ImmediateTensorHandlePtr* out);

}  // namespace internal
}  // namespace tensorflow