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116 lines
3.2 KiB
116 lines
3.2 KiB
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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from paddle.trainer.PyDataProvider2 import *
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# Note that each config should has an independent provider
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# in current design of PyDataProvider2.
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#######################################################
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data = [
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[[[1, 3, 2], [4, 5, 2]], 0],
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[[[0, 2], [2, 5], [0, 1, 2]], 1],
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]
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# Used for sequence_nest_rnn.conf
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@provider(
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input_types=[integer_value_sub_sequence(10), integer_value(3)],
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should_shuffle=False)
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def process_subseq(settings, file_name):
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for d in data:
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yield d
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# Used for sequence_rnn.conf
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@provider(
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input_types=[integer_value_sequence(10), integer_value(3)],
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should_shuffle=False)
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def process_seq(settings, file_name):
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for d in data:
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seq = []
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for subseq in d[0]:
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seq += subseq
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yield seq, d[1]
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# Used for sequence_nest_rnn_multi_input.conf
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@provider(
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input_types=[integer_value_sub_sequence(10), integer_value(3)],
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should_shuffle=False)
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def process_subseq2(settings, file_name):
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for d in data:
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yield d
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# Used for sequence_rnn_multi_input.conf
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@provider(
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input_types=[integer_value_sequence(10), integer_value(3)],
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should_shuffle=False)
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def process_seq2(settings, file_name):
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for d in data:
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seq = []
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for subseq in d[0]:
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seq += subseq
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yield seq, d[1]
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###########################################################
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data2 = [
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[[[1, 2], [4, 5, 2]], [[5, 4, 1], [3, 1]], 0],
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[[[0, 2], [2, 5], [0, 1, 2]], [[1, 5], [4], [2, 3, 6, 1]], 1],
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]
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# Used for sequence_nest_rnn_multi_unequalength_inputs.conf
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@provider(
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input_types=[
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integer_value_sub_sequence(10), integer_value_sub_sequence(10),
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integer_value(2)
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],
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should_shuffle=False)
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def process_unequalength_subseq(settings, file_name):
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for d in data2:
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yield d
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# Used for sequence_rnn_multi_unequalength_inputs.conf
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@provider(
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input_types=[
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integer_value_sequence(10), integer_value_sequence(10), integer_value(2)
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],
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should_shuffle=False)
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def process_unequalength_seq(settings, file_name):
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for d in data2:
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words1 = reduce(lambda x, y: x + y, d[0])
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words2 = reduce(lambda x, y: x + y, d[1])
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yield words1, words2, d[2]
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###########################################################
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data3 = [
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[[[1, 2], [4, 5, 2]], [1, 2], 0],
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[[[0, 2], [2, 5], [0, 1, 2]], [2, 3, 0], 1],
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]
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# Used for sequence_nest_mixed_inputs.conf
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@provider(
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input_types=[
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integer_value_sub_sequence(10), integer_value_sequence(10),
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integer_value(2)
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],
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should_shuffle=False)
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def process_mixed(settings, file_name):
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for d in data3:
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yield d
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