import unittest
import numpy as np
from op_test import OpTest


class ElementwiseDivOp(OpTest):
    def setUp(self):
        self.op_type = "elementwise_div"
        """ Warning
        CPU gradient check error!
        'X': np.random.random((32,84)).astype("float32"),
        'Y': np.random.random((32,84)).astype("float32")
        """
        self.inputs = {
            'X': np.random.uniform(0.1, 1, [13, 17]).astype("float32"),
            'Y': np.random.uniform(0.1, 1, [13, 17]).astype("float32")
        }
        self.outputs = {'Out': np.divide(self.inputs['X'], self.inputs['Y'])}

    def test_check_output(self):
        self.check_output()

    def test_check_grad_normal(self):
        self.check_grad(['X', 'Y'], 'Out', max_relative_error=0.05)

    def test_check_grad_ingore_x(self):
        self.check_grad(
            ['Y'], 'Out', max_relative_error=0.05, no_grad_set=set("X"))

    def test_check_grad_ingore_y(self):
        self.check_grad(
            ['X'], 'Out', max_relative_error=0.05, no_grad_set=set('Y'))


class TestElementwiseDivOp_Vector(ElementwiseDivOp):
    def setUp(self):
        self.op_type = "elementwise_div"
        self.inputs = {
            'X': np.random.uniform(0.1, 1, [32]).astype("float32"),
            'Y': np.random.uniform(0.1, 1, [32]).astype("float32")
        }
        self.outputs = {'Out': np.divide(self.inputs['X'], self.inputs['Y'])}


class TestElementwiseDivOp_broadcast_0(ElementwiseDivOp):
    def setUp(self):
        self.op_type = "elementwise_div"
        self.inputs = {
            'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"),
            'Y': np.random.uniform(0.1, 1, [2]).astype("float32")
        }

        self.attrs = {'axis': 0}
        self.outputs = {
            'Out':
            np.divide(self.inputs['X'], self.inputs['Y'].reshape(2, 1, 1))
        }


class TestElementwiseDivOp_broadcast_1(ElementwiseDivOp):
    def setUp(self):
        self.op_type = "elementwise_div"
        self.inputs = {
            'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"),
            'Y': np.random.uniform(0.1, 1, [3]).astype("float32")
        }

        self.attrs = {'axis': 1}
        self.outputs = {
            'Out':
            np.divide(self.inputs['X'], self.inputs['Y'].reshape(1, 3, 1))
        }


class TestElementwiseDivOp_broadcast_2(ElementwiseDivOp):
    def setUp(self):
        self.op_type = "elementwise_div"
        self.inputs = {
            'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"),
            'Y': np.random.uniform(0.1, 1, [4]).astype("float32")
        }

        self.outputs = {
            'Out':
            np.divide(self.inputs['X'], self.inputs['Y'].reshape(1, 1, 4))
        }


class TestElementwiseDivOp_broadcast_3(ElementwiseDivOp):
    def setUp(self):
        self.op_type = "elementwise_div"
        self.inputs = {
            'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float32"),
            'Y': np.random.uniform(0.1, 1, [3, 4]).astype("float32")
        }

        self.attrs = {'axis': 1}
        self.outputs = {
            'Out':
            np.divide(self.inputs['X'], self.inputs['Y'].reshape(1, 3, 4, 1))
        }


if __name__ == '__main__':
    unittest.main()