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import os
import numpy as np
import tensorflow as tf

'''
This file is used to obtain the pb model and data for the operator.
There are four steps to this file.
One example is shown in the following.
'''


def TFGenModelData(gen_pb_model=True):
    os.environ["CUDA_VISIBLE_DEVICES"] = ''

    with tf.Session(graph=tf.Graph()) as sess:
        '''
        STEP 1: plz input the tensor shapes
        shapes must be 4D, and the first dim means batch_size
        '''
        shape_x = (7, 2, 3, 4)
        shape_y = (7, 2, 3, 4)
        coor_x = tf.placeholder(tf.float32, shape=shape_x, name='x')
        coor_y = tf.placeholder(tf.float32, shape=shape_y, name='y')

        '''
        STEP 2: plz input the OP name
        '''
        name = "pow"

        '''
        STEP 3: plz input the specific tensorflow OP function
        '''
        tf_op = tf.pow(coor_x, coor_y, name=name)

        '''
        STEP 4:  plz config the OP data
        '''

        # input_x = np.random.rand(*shape_x).astype(np.float32, copy=False)\
        #  - 0.5
        # input_y = np.random.rand(*shape_y).astype(np.float32, copy=False)

        input_x = np.random.randint(1, 5, size=shape_x).astype(np.float32,
                                                               copy=False) - 8
        input_y = np.random.randint(1, 5, size=shape_y).astype(np.float32,
                                                               copy=False)

        feed_dict = {coor_x: input_x, coor_y: input_y}
        # feed_dict = {x: input_x}
        sess.run(tf.global_variables_initializer())
        expect = sess.run(tf_op, feed_dict)

        if gen_pb_model:
            current_path = os.getcwd()
            os.chdir("./common/op_verify_files/tensorflow_files")
            # ensure that there is only one om and pb in the
            # tensorflow_files directory
            for filename in os.listdir("./"):
                if filename.endswith(".om") or filename.endswith(".pb"):
                    os.remove(filename)
            graph = tf.compat.v1.graph_util.convert_variables_to_constants(
                sess, sess.graph_def, [name])
            with tf.gfile.FastGFile('tf_' + name + '.pb', mode='wb') as g_f:
                g_f.write(graph.SerializeToString())
            os.chdir(current_path)

    return [input_x, input_y], [expect, ]


if __name__ == "__main__":
    TFGenModelData()