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106 lines
3.2 KiB
106 lines
3.2 KiB
import unittest
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import numpy as np
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from op_test import OpTest
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class ElementwiseDivOp(OpTest):
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def setUp(self):
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self.op_type = "elementwise_div"
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""" Warning
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CPU gradient check error!
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'X': np.random.random((32,84)).astype("float32"),
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'Y': np.random.random((32,84)).astype("float32")
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"""
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self.inputs = {
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'X': np.random.uniform(0.1, 1, [13, 17]).astype("float32"),
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'Y': np.random.uniform(0.1, 1, [13, 17]).astype("float32")
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}
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self.outputs = {'Out': np.divide(self.inputs['X'], self.inputs['Y'])}
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def test_check_output(self):
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self.check_output()
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def test_check_grad_normal(self):
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self.check_grad(['X', 'Y'], 'Out', max_relative_error=0.05)
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def test_check_grad_ingore_x(self):
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self.check_grad(
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['Y'], 'Out', max_relative_error=0.05, no_grad_set=set("X"))
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def test_check_grad_ingore_y(self):
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self.check_grad(
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['X'], 'Out', max_relative_error=0.05, no_grad_set=set('Y'))
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class TestElementwiseDivOp_Vector(ElementwiseDivOp):
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def setUp(self):
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self.op_type = "elementwise_div"
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self.inputs = {
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'X': np.random.uniform(0.1, 1, [32]).astype("float32"),
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'Y': np.random.uniform(0.1, 1, [32]).astype("float32")
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}
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self.outputs = {'Out': np.divide(self.inputs['X'], self.inputs['Y'])}
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class TestElementwiseDivOp_broadcast_0(ElementwiseDivOp):
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def setUp(self):
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self.op_type = "elementwise_div"
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self.inputs = {
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'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"),
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'Y': np.random.uniform(0.1, 1, [2]).astype("float32")
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}
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self.attrs = {'axis': 0}
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self.outputs = {
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'Out':
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np.divide(self.inputs['X'], self.inputs['Y'].reshape(2, 1, 1))
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}
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class TestElementwiseDivOp_broadcast_1(ElementwiseDivOp):
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def setUp(self):
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self.op_type = "elementwise_div"
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self.inputs = {
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'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"),
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'Y': np.random.uniform(0.1, 1, [3]).astype("float32")
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}
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self.attrs = {'axis': 1}
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self.outputs = {
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'Out':
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np.divide(self.inputs['X'], self.inputs['Y'].reshape(1, 3, 1))
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}
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class TestElementwiseDivOp_broadcast_2(ElementwiseDivOp):
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def setUp(self):
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self.op_type = "elementwise_div"
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self.inputs = {
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'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"),
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'Y': np.random.uniform(0.1, 1, [4]).astype("float32")
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}
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self.outputs = {
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'Out':
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np.divide(self.inputs['X'], self.inputs['Y'].reshape(1, 1, 4))
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}
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class TestElementwiseDivOp_broadcast_3(ElementwiseDivOp):
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def setUp(self):
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self.op_type = "elementwise_div"
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self.inputs = {
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'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float32"),
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'Y': np.random.uniform(0.1, 1, [3, 4]).astype("float32")
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}
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self.attrs = {'axis': 1}
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self.outputs = {
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'Out':
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np.divide(self.inputs['X'], self.inputs['Y'].reshape(1, 3, 4, 1))
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}
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if __name__ == '__main__':
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unittest.main()
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