/*
 * Copyright (c) 2016-2019, The Linux Foundation. All rights reserved.
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 * modification, are permitted (subject to the limitations in the
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 *      notice, this list of conditions and the following disclaimer.
 *
 *    * Redistributions in binary form must reproduce the above
 *      copyright notice, this list of conditions and the following
 *      disclaimer in the documentation and/or other materials provided
 *      with the distribution.
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 *    * Neither the name of The Linux Foundation nor the names of its
 *      contributors may be used to endorse or promote products derived
 *      from this software without specific prior written permission.
 *
 * NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE
 * GRANTED BY THIS LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT
 * HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED
 * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
 * MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
 * IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
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#include <nn_graph.h>
#include <string.h>
#include <quantize.h>
#include <math.h>
//
// copies one int from its second input to its output.
//


static int rank_execute(struct nn_node *self, struct nn_graph *nn)
{
	//const struct tensor *in_tensor = self->inputs[0];
	const struct tensor *true_rank_tensor = self->inputs[1];
	struct tensor *out_tensor = self->outputs[0];
	int rank = tensor_get_int32(true_rank_tensor,0);

	logmsg(nn,2,"rank execute. self=%p ",self);

	if( tensor_out_prepare_normal( out_tensor, 1,1,1,1, NN_TYPE_INT32)!= 0 )
		return errlog(nn,"out too small");

	tensor_set_int32(out_tensor,0,rank);

	logmsg(nn,2,"rank %p done",self);
	return 0;
}


struct nn_node_ops nn_ops_for_Rank_int32 = {
	.execute = rank_execute,
	.check = NULL,
	.ctor = node_alloc_common,
	.dtor = node_free_common,
	.n_inputs = NN_IOCOUNT(2),
	.n_outputs = NN_IOCOUNT(1),
};

