You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
95 lines
2.7 KiB
95 lines
2.7 KiB
import unittest
|
|
import numpy as np
|
|
from op_test import OpTest
|
|
|
|
|
|
class ElementwiseMulOp(OpTest):
|
|
def setUp(self):
|
|
self.op_type = "elementwise_mul"
|
|
self.inputs = {
|
|
'X': np.random.uniform(0.1, 1, [13, 17]).astype("float64"),
|
|
'Y': np.random.uniform(0.1, 1, [13, 17]).astype("float64")
|
|
}
|
|
self.outputs = {'Out': np.multiply(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')
|
|
|
|
def test_check_grad_ingore_x(self):
|
|
self.check_grad(['Y'], 'Out', no_grad_set=set("X"))
|
|
|
|
def test_check_grad_ingore_y(self):
|
|
self.check_grad(['X'], 'Out', no_grad_set=set('Y'))
|
|
|
|
|
|
class TestElementwiseMulOp_Vector(ElementwiseMulOp):
|
|
def setUp(self):
|
|
self.op_type = "elementwise_mul"
|
|
self.inputs = {
|
|
'X': np.random.random((32, )).astype("float64"),
|
|
'Y': np.random.random((32, )).astype("float64")
|
|
}
|
|
self.outputs = {'Out': np.multiply(self.inputs['X'], self.inputs['Y'])}
|
|
|
|
|
|
class TestElementwiseMulOp_broadcast_0(ElementwiseMulOp):
|
|
def setUp(self):
|
|
self.op_type = "elementwise_mul"
|
|
self.inputs = {
|
|
'X': np.random.rand(2, 3, 4).astype(np.float64),
|
|
'Y': np.random.rand(2).astype(np.float64)
|
|
}
|
|
|
|
self.attrs = {'axis': 0}
|
|
self.outputs = {
|
|
'Out': self.inputs['X'] * self.inputs['Y'].reshape(2, 1, 1)
|
|
}
|
|
|
|
|
|
class TestElementwiseMulOp_broadcast_1(ElementwiseMulOp):
|
|
def setUp(self):
|
|
self.op_type = "elementwise_mul"
|
|
self.inputs = {
|
|
'X': np.random.rand(2, 3, 4).astype(np.float64),
|
|
'Y': np.random.rand(3).astype(np.float64)
|
|
}
|
|
|
|
self.attrs = {'axis': 1}
|
|
self.outputs = {
|
|
'Out': self.inputs['X'] * self.inputs['Y'].reshape(1, 3, 1)
|
|
}
|
|
|
|
|
|
class TestElementwiseMulOp_broadcast_2(ElementwiseMulOp):
|
|
def setUp(self):
|
|
self.op_type = "elementwise_mul"
|
|
self.inputs = {
|
|
'X': np.random.rand(2, 3, 4).astype(np.float64),
|
|
'Y': np.random.rand(4).astype(np.float64)
|
|
}
|
|
|
|
self.outputs = {
|
|
'Out': self.inputs['X'] * self.inputs['Y'].reshape(1, 1, 4)
|
|
}
|
|
|
|
|
|
class TestElementwiseMulOp_broadcast_3(ElementwiseMulOp):
|
|
def setUp(self):
|
|
self.op_type = "elementwise_mul"
|
|
self.inputs = {
|
|
'X': np.random.rand(2, 3, 4, 5).astype(np.float64),
|
|
'Y': np.random.rand(3, 4).astype(np.float64)
|
|
}
|
|
|
|
self.attrs = {'axis': 1}
|
|
self.outputs = {
|
|
'Out': self.inputs['X'] * self.inputs['Y'].reshape(1, 3, 4, 1)
|
|
}
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|