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87 lines
2.3 KiB
87 lines
2.3 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 SeqPoolType(OpTest):
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AVERAGE = 0
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SUM = 1
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SQRT = 2
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MAX = 3
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LAST = 4
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FIRST = 5
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class TestSeqAvgPool(OpTest):
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def set_data(self):
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self.op_type = 'sequence_pool'
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# one level, batch size is 4
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x = np.random.uniform(0.1, 1, [11, 23]).astype('float32')
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lod = [[0, 4, 5, 8, 11]]
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self.inputs = {'X': (x, lod)}
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out = np.zeros((4, 23)).astype('float32')
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self.outputs = {'Out': out}
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def compute(self):
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self.attrs = {'strategy': SeqPoolType.AVERAGE}
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x, lod = self.inputs['X']
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out = self.outputs['Out']
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for i in range(4):
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sub_x = x[lod[0][i]:lod[0][i + 1], :]
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out[i] = sub_x.mean(axis=0)
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def setUp(self):
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self.set_data()
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self.compute()
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(["X"], "Out")
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class TestSeqAvgPool2D(TestSeqAvgPool):
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def set_data(self):
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self.op_type = 'sequence_pool'
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# one level, batch size is 4
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x = np.random.uniform(0.1, 1, [13, 3, 17]).astype('float32')
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lod = [[0, 4, 5, 8, 13]]
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self.inputs = {'X': (x, lod)}
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out = np.zeros((4, 3, 17)).astype('float32')
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self.outputs = {'Out': out}
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def compute(self):
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self.attrs = {'strategy': SeqPoolType.AVERAGE}
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x, lod = self.inputs['X']
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out = self.outputs['Out']
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for i in range(4):
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sub_x = np.reshape(x[lod[0][i]:lod[0][i + 1], :], (-1, 3 * 17))
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out[i] = np.reshape(sub_x.mean(axis=0), (3, 17))
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class TestSeqSumPool(TestSeqAvgPool):
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def compute(self):
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self.attrs = {'strategy': SeqPoolType.SUM}
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x, lod = self.inputs['X']
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out = self.outputs['Out']
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for i in range(4):
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sub_x = x[lod[0][i]:lod[0][i + 1], :]
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out[i] = sub_x.sum(axis=0)
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class TestSeqSumPool2D(TestSeqAvgPool2D):
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def compute(self):
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self.attrs = {'strategy': SeqPoolType.SUM}
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x, lod = self.inputs['X']
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out = self.outputs['Out']
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for i in range(4):
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sub_x = np.reshape(x[lod[0][i]:lod[0][i + 1], :], (-1, 3 * 17))
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out[i] = np.reshape(sub_x.sum(axis=0), (3, 17))
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if __name__ == '__main__':
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unittest.main()
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