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143 lines
4.8 KiB
143 lines
4.8 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from op_test import OpTest
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import paddle.fluid.core as core
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from paddle.fluid.op import Operator
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class TestLookupTableOp(OpTest):
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def setUp(self):
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self.op_type = "lookup_table"
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table = np.random.random((17, 31)).astype("float32")
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ids = np.random.randint(0, 17, 4).astype("int64")
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ids_expand = np.expand_dims(ids, axis=1)
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self.inputs = {'W': table, 'Ids': ids_expand}
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self.outputs = {'Out': table[ids]}
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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(['W'], 'Out', no_grad_set=set('Ids'))
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class TestLookupTableOpWithPadding(TestLookupTableOp):
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def test_check_output(self):
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ids = np.squeeze(self.inputs['Ids'])
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padding_idx = np.random.choice(ids, 1)[0]
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self.outputs['Out'][ids == padding_idx] = np.zeros(31)
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self.attrs = {'padding_idx': long(padding_idx)}
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self.check_output()
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def test_check_grad(self):
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# Since paddings are not trainable and fixed in forward, the gradient of
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# paddings makes no sense and we don't test the gradient here.
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pass
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class TestLookupTableIdsIsSelectedRows(OpTest):
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def check_with_place(self, place):
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scope = core.Scope()
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# create and initialize Variable
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height = 10
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rows = [0, 4, 4, 7]
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row_numel = 12
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# create and initialize W Variable
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W = scope.var('W').get_tensor()
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W_array = np.full((height, row_numel), 1.0).astype("float32")
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for i in range(height):
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W_array[i] *= i
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W.set(W_array, place)
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# create and initialize Ids Variable
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ids_selected_rows = scope.var('Ids').get_selected_rows()
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ids_selected_rows.set_height(len(rows))
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ids_selected_rows.set_rows(rows)
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np_array = np.ones((len(rows), row_numel)).astype("float32")
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ids_tensor = ids_selected_rows.get_tensor()
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ids_tensor.set(np_array, place)
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# create Out Variable
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Out = scope.var('Out').get_selected_rows()
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# create and run lookup_table operator
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concat_rows_op = Operator("lookup_table", W='W', Ids='Ids', Out='Out')
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concat_rows_op.run(scope, place)
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# get result from Out
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Out_tensor = Out.get_tensor()
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result_array = np.array(Out_tensor)
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# all(): return True if all elements of the iterable are true (or if the iterable is empty)
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for idx, row in enumerate(rows):
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assert (row == result_array[idx]).all()
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def test_concat_rows(self):
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places = [core.CPUPlace()]
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if core.is_compiled_with_cuda():
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places.append(core.CUDAPlace(0))
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for place in places:
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self.check_with_place(place)
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class TestLookupTableWIsSelectedRows(OpTest):
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def check_with_place(self, place):
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scope = core.Scope()
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# create and initialize Id Variable
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ids_tensor = scope.var('Ids').get_tensor()
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ids_array = np.array([[0], [4], [3], [5]]).astype("int64")
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ids_tensor.set(ids_array, place)
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# create and initialize W Variable
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rows = [0, 1, 2, 3, 4, 5, 6]
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row_numel = 12
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w_selected_rows = scope.var('W').get_selected_rows()
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w_selected_rows.set_height(len(rows))
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w_selected_rows.set_rows(rows)
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w_array = np.ones((len(rows), row_numel)).astype("float32")
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for i in range(len(rows)):
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w_array[i] *= i
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w_tensor = w_selected_rows.get_tensor()
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w_tensor.set(w_array, place)
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# create Out Variable
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out_tensor = scope.var('Out').get_tensor()
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# create and run lookup_table operator
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lookup_table = Operator("lookup_table", W='W', Ids='Ids', Out='Out')
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lookup_table.run(scope, place)
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# get result from Out
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result_array = np.array(out_tensor)
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# all(): return True if all elements of the iterable are true (or if the iterable is empty)
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for idx, row in enumerate(ids_array):
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assert (row[0] == result_array[idx]).all()
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def test_w_is_selected_rows(self):
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places = [core.CPUPlace()]
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# currently only support CPU
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for place in places:
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self.check_with_place(place)
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if __name__ == "__main__":
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unittest.main()
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