193 lines
13 KiB
C++
193 lines
13 KiB
C++
/**
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* Copyright 2019-2021 Huawei Technologies Co., Ltd
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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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*/
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#include "transform/graph_ir/op_declare/rnn_declare.h"
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namespace mindspore::transform {
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// BasicLSTMCell
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INPUT_MAP(BasicLSTMCell) = {
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{1, INPUT_DESC(x)}, {2, INPUT_DESC(h)}, {3, INPUT_DESC(c)}, {4, INPUT_DESC(w)}, {5, INPUT_DESC(b)}};
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// 输入映射，共五个，x索引为1，h索引为2，c索引为3，w索引为4，b索引为5
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ATTR_MAP(BasicLSTMCell) = {{"keep_prob", ATTR_DESC(keep_prob, AnyTraits<float>())},
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{"forget_bias", ATTR_DESC(forget_bias, AnyTraits<float>())},
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{"state_is_tuple", ATTR_DESC(state_is_tuple, AnyTraits<bool>())},
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{"activation", ATTR_DESC(activation, AnyTraits<std::string>())}};
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// 属性映射，列出了"keep_prob"、"forget_bias"、"state_is_tuple"、"activation"四个属性，类型分别为bool和std::string
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OUTPUT_MAP(BasicLSTMCell) = {{0, OUTPUT_DESC(ct)}, {1, OUTPUT_DESC(ht)}, {2, OUTPUT_DESC(it)}, {3, OUTPUT_DESC(jt)},
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{4, OUTPUT_DESC(ft)}, {5, OUTPUT_DESC(ot)}, {6, OUTPUT_DESC(tanhct)}}
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// 输出映射，共七个，cty索引为0，ht索引为1，it索引为2，jt索引为3，ft索引为4，ot索引为5，tanhct索引为6
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REG_ADPT_DESC(BasicLSTMCell, kNameBasicLSTMCell, ADPT_DESC(BasicLSTMCell))
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// 注册BasicLSTMCell操作的适配器描述kNameBasicLSTMCell
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// BasicLSTMCellInputGrad
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INPUT_MAP(BasicLSTMCellInputGrad) = {{1, INPUT_DESC(dgate)}, {2, INPUT_DESC(w)}};
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// 输入映射，共两个，dgate索引为1，w索引为2
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ATTR_MAP(BasicLSTMCellInputGrad) = {{"keep_prob", ATTR_DESC(keep_prob, AnyTraits<float>())}};
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// 属性映射，列出了"keep_prob"属性，类型为float
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OUTPUT_MAP(BasicLSTMCellInputGrad) = {{0, OUTPUT_DESC(dxt)}, {1, OUTPUT_DESC(dht)}};
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// 输出映射，共两个，dxt索引为0，dht索引为1
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REG_ADPT_DESC(BasicLSTMCellInputGrad, kNameBasicLSTMCellInputGrad, ADPT_DESC(BasicLSTMCellInputGrad))
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// 注册BasicLSTMCellInputGrad操作的适配器描述kNameBasicLSTMCellInputGrad
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// BasicLSTMCellWeightGrad
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INPUT_MAP(BasicLSTMCellWeightGrad) = {{1, INPUT_DESC(x)}, {2, INPUT_DESC(h)}, {3, INPUT_DESC(dgate)}};
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// 输入映射，共三个，dgate索引为1，w索引为2，dgate索引为3
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ATTR_MAP(BasicLSTMCellWeightGrad) = EMPTY_ATTR_MAP;
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//属性映射，空
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OUTPUT_MAP(BasicLSTMCellWeightGrad) = {{0, OUTPUT_DESC(dw)}, {1, OUTPUT_DESC(db)}};
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// 输出映射，共两个，dw索引为0，db索引为1
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REG_ADPT_DESC(BasicLSTMCellWeightGrad, kNameBasicLSTMCellWeightGrad, ADPT_DESC(BasicLSTMCellWeightGrad))
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// 注册BasicLSTMCellWeightGrad操作的适配器描述kNameBasicLSTMCellWeightGrad
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// BasicLSTMCellCStateGrad
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INPUT_MAP(BasicLSTMCellCStateGrad) = {{1, INPUT_DESC(c)}, {2, INPUT_DESC(dht)}, {3, INPUT_DESC(dct)},
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{4, INPUT_DESC(it)}, {5, INPUT_DESC(jt)}, {6, INPUT_DESC(ft)},
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{7, INPUT_DESC(ot)}, {8, INPUT_DESC(tanhct)}};
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// 输入映射，共八个，c索引为1，dht索引为2，dct索引为3，it索引为4，jt索引为5，ft索引为6，ot索引为7，tanhct索引为8
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ATTR_MAP(BasicLSTMCellCStateGrad) = {{"forget_bias", ATTR_DESC(forget_bias, AnyTraits<float>())},
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{"activation", ATTR_DESC(activation, AnyTraits<std::string>())}};
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// 属性映射，列出了"forget_bias"和"activation"属性，类型分别为float和std::string
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OUTPUT_MAP(BasicLSTMCellCStateGrad) = {{0, OUTPUT_DESC(dgate)}, {1, OUTPUT_DESC(dct_1)}};
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// 输出映射，共两个，dgate索引为0，dct_1索引为1
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REG_ADPT_DESC(BasicLSTMCellCStateGrad, kNameBasicLSTMCellCStateGrad, ADPT_DESC(BasicLSTMCellCStateGrad))
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// 注册BasicLSTMCellCStateGrad操作的适配器描述kNameBasicLSTMCellCStateGrad
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// LSTMInputGrad
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INPUT_MAP(LSTMInputGrad) = {{1, INPUT_DESC(w)}, {2, INPUT_DESC(init_c)}, {3, INPUT_DESC(c)}, {4, INPUT_DESC(dy)},
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{5, INPUT_DESC(dh)}, {6, INPUT_DESC(dc)}, {7, INPUT_DESC(i)}, {8, INPUT_DESC(j)},
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{9, INPUT_DESC(f)}, {10, INPUT_DESC(o)}, {11, INPUT_DESC(tanhct)}};
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//输入映射，共十一个，w索引为1，init_c索引为2，di索引为3，dy索引为4，dh索引为5，dc索引为6，i索引为7，j索引为8，f索引为9，o索引为10，tanhct索引为11
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ATTR_MAP(LSTMInputGrad) = EMPTY_ATTR_MAP;
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// 属性映射，空
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OUTPUT_MAP(LSTMInputGrad) = {
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{0, OUTPUT_DESC(dx)}, {1, OUTPUT_DESC(dh_prev)}, {2, OUTPUT_DESC(dc_prev)}, {4, OUTPUT_DESC(dgate)}};
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// 输出映射，共四个，dh_prev索引为1，dc_prev索引为2，dgate索引为4
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REG_ADPT_DESC(LSTMInputGrad, kNameLSTMInputGrad, ADPT_DESC(LSTMInputGrad))
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// 注册LSTMInputGrad操作的适配器描述kNameLSTMInputGrad
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// DynamicRNN
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INPUT_MAP(DynamicRNN) = {{1, INPUT_DESC(x)}, {2, INPUT_DESC(w)}, {3, INPUT_DESC(b)},
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{4, INPUT_DESC(seq_length)}, {5, INPUT_DESC(init_h)}, {6, INPUT_DESC(init_c)},
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{7, INPUT_DESC(wci)}, {8, INPUT_DESC(wcf)}, {9, INPUT_DESC(wco)},
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{10, INPUT_DESC(mask)}};
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// 输入映射，共十个，x索引为1，w索引为2，b索引为3，seq_length索引为4，init_h索引为5，init_c索引为6，wci索引为7，wcf索引为8，wco索引为9，mask索引为10
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ATTR_MAP(DynamicRNN) = {{"cell_type", ATTR_DESC(cell_type, AnyTraits<std::string>())},
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{"direction", ATTR_DESC(direction, AnyTraits<std::string>())},
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{"cell_depth", ATTR_DESC(cell_depth, AnyTraits<int64_t>())},
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{"use_peephole", ATTR_DESC(use_peephole, AnyTraits<bool>())},
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{"keep_prob", ATTR_DESC(keep_prob, AnyTraits<float>())},
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{"cell_clip", ATTR_DESC(cell_clip, AnyTraits<float>())},
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{"num_proj", ATTR_DESC(num_proj, AnyTraits<int64_t>())},
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{"time_major", ATTR_DESC(time_major, AnyTraits<bool>())},
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{"ivation", ATTR_DESC(activation, AnyTraits<std::string>())},
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{"forget_bias", ATTR_DESC(forget_bias, AnyTraits<float>())},
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{"is_training", ATTR_DESC(is_training, AnyTraits<bool>())}};
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// 属性映射，列出了"cell_type""ivation"和"direction"属性，类型为std::string
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//"cell_depth"和"num_proj",类型为int64_t
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//"use_peephole""is_training"和"time_major"，类型为bool
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//"keep_prob""cell_clip""forget_bias"，类型为float
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OUTPUT_MAP(DynamicRNN) = {{0, OUTPUT_DESC(y)}, {1, OUTPUT_DESC(output_h)}, {2, OUTPUT_DESC(output_c)},
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{3, OUTPUT_DESC(i)}, {4, OUTPUT_DESC(j)}, {5, OUTPUT_DESC(f)},
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{6, OUTPUT_DESC(o)}, {7, OUTPUT_DESC(tanhc)}};
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// 输出映射，共十个，x索引为1，w索引为2，b索引为3，seq_length索引为4，init_h索引为5，init_c索引为6，wci索引为7，wcf索引为8，wco索引为9，mask索引为10
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REG_ADPT_DESC(DynamicRNN, kNameDynamicRNN, ADPT_DESC(DynamicRNN))
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// 注册DynamicRNN操作的适配器描述kNameDynamicRNN
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// DynamicRNNGrad
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INPUT_MAP(DynamicRNNGrad) = {
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{1, INPUT_DESC(x)}, {2, INPUT_DESC(w)}, {3, INPUT_DESC(b)}, {4, INPUT_DESC(y)},
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{5, INPUT_DESC(init_h)}, {6, INPUT_DESC(init_c)}, {7, INPUT_DESC(h)}, {8, INPUT_DESC(c)},
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{9, INPUT_DESC(dy)}, {10, INPUT_DESC(dh)}, {11, INPUT_DESC(dc)}, {12, INPUT_DESC(i)},
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{13, INPUT_DESC(j)}, {14, INPUT_DESC(f)}, {15, INPUT_DESC(o)}, {16, INPUT_DESC(tanhct)}};
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// 输入映射，共十个，x索引为1，w索引为2，b索引为3，y索引为4，init_h索引为5，init_c索引为6，h索引为7，c索引为8，dy索引为9，dh索引为10,dc索引为11，i索引为12
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//j索引为13，f索引为14，o索引为15，tanhct索引为16
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ATTR_MAP(DynamicRNNGrad) = {{"cell_type", ATTR_DESC(cell_type, AnyTraits<std::string>())},
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{"direction", ATTR_DESC(direction, AnyTraits<std::string>())},
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{"cell_depth", ATTR_DESC(cell_depth, AnyTraits<int64_t>())},
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{"use_peephole", ATTR_DESC(use_peephole, AnyTraits<bool>())},
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{"keep_prob", ATTR_DESC(keep_prob, AnyTraits<float>())},
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{"cell_clip", ATTR_DESC(cell_clip, AnyTraits<float>())},
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{"num_proj", ATTR_DESC(num_proj, AnyTraits<int64_t>())},
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{"time_major", ATTR_DESC(time_major, AnyTraits<bool>())},
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{"forget_bias", ATTR_DESC(forget_bias, AnyTraits<float>())}};
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// 属性映射，列出了"cell_type"和"direction"属性，类型为std::string
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//"cell_depth"和"num_proj",类型为int64_t
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//"use_peephole""is_training"和"time_major"，类型为bool
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//"keep_prob""cell_clip""forget_bias"，类型为float
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OUTPUT_MAP(DynamicRNNGrad) = {{0, OUTPUT_DESC(dw)},
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{1, OUTPUT_DESC(db)},
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{2, OUTPUT_DESC(dx)},
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{3, OUTPUT_DESC(dh_prev)},
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{4, OUTPUT_DESC(dc_prev)}};
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// 输出映射，共五个，dw索引为0，db索引为1，dh_prev索引为2，dh_prev索引为3，dc_prev索引为4
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REG_ADPT_DESC(DynamicRNNGrad, kNameDynamicRNNGrad, ADPT_DESC(DynamicRNNGrad))
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// 注册DynamicRNNGrad操作的适配器描述kNameDynamicRNNGrad
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// DynamicGRUV2
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INPUT_MAP(DynamicGRUV2) = {{1, INPUT_DESC(x)}, {2, INPUT_DESC(weight_input)}, {3, INPUT_DESC(weight_hidden)},
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{4, INPUT_DESC(bias_input)}, {5, INPUT_DESC(bias_hidden)}, {6, INPUT_DESC(seq_length)},
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{7, INPUT_DESC(init_h)}};
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// 输入映射，共七个，x索引为1，weight_input索引为2，weight_hidden索引为3，bias_input索引为4，bias_hidden索引为5，seq_length索引为6，init_h索引为7
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ATTR_MAP(DynamicGRUV2) = {{"direction", ATTR_DESC(direction, AnyTraits<std::string>())},
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{"cell_depth", ATTR_DESC(cell_depth, AnyTraits<int64_t>())},
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{"keep_prob", ATTR_DESC(keep_prob, AnyTraits<float>())},
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{"cell_clip", ATTR_DESC(cell_clip, AnyTraits<float>())},
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{"num_proj", ATTR_DESC(num_proj, AnyTraits<int64_t>())},
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{"time_major", ATTR_DESC(time_major, AnyTraits<bool>())},
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{"activation", ATTR_DESC(activation, AnyTraits<std::string>())},
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{"gate_order", ATTR_DESC(gate_order, AnyTraits<std::string>())},
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{"reset_after", ATTR_DESC(reset_after, AnyTraits<bool>())},
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{"is_training", ATTR_DESC(is_training, AnyTraits<bool>())}};
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// 属性映射，列出了"direction"和"activation""gate_order"属性，类型为std::string
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//"cell_depth"和"num_proj",类型为int64_t
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//"reset_after""is_training"和"time_major"，类型为bool
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//"keep_prob""cell_clip""forget_bias"，类型为float
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OUTPUT_MAP(DynamicGRUV2) = {{0, OUTPUT_DESC(y)}, {1, OUTPUT_DESC(output_h)}, {2, OUTPUT_DESC(update)},
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{3, OUTPUT_DESC(reset)}, {4, OUTPUT_DESC(new)}, {5, OUTPUT_DESC(hidden_new)}};
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// 输入映射，共六个，y索引为0，output_h索引为1，update索引为2，reset索引为3，new索引为4，hidden_new索引为5
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REG_ADPT_DESC(DynamicGRUV2, kNameDynamicGRUV2, ADPT_DESC(DynamicGRUV2))
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// 注册DynamicGRUV2操作的适配器描述kNameDynamicGRUV2
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//
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// DynamicGRUV2Grad
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INPUT_MAP(DynamicGRUV2Grad) = {
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{1, INPUT_DESC(x)}, {2, INPUT_DESC(weight_input)}, {3, INPUT_DESC(weight_hidden)},
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{4, INPUT_DESC(y)}, {5, INPUT_DESC(init_h)}, {6, INPUT_DESC(h)},
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{7, INPUT_DESC(dy)}, {8, INPUT_DESC(dh)}, {9, INPUT_DESC(update)},
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{10, INPUT_DESC(reset)}, {11, INPUT_DESC(new)}, {12, INPUT_DESC(hidden_new)},
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{13, INPUT_DESC(seq_length)}, {14, INPUT_DESC(mask)}};
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// 输入映射，共十四个，x索引为1，weight_input索引为2，weight_hidden索引为3，y索引为4，init_h索引为5，h索引为6，dy索引为7，dh索引为8，
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//update索引为9，reset索引为10，new索引为11，hidden_new索引为12，seq_length索引为13，mask索引为14
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ATTR_MAP(DynamicGRUV2Grad) = {{"direction", ATTR_DESC(direction, AnyTraits<std::string>())},
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{"cell_depth", ATTR_DESC(cell_depth, AnyTraits<int64_t>())},
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{"keep_prob", ATTR_DESC(keep_prob, AnyTraits<float>())},
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{"cell_clip", ATTR_DESC(cell_clip, AnyTraits<float>())},
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{"num_proj", ATTR_DESC(num_proj, AnyTraits<int64_t>())},
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{"time_major", ATTR_DESC(time_major, AnyTraits<bool>())},
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{"gate_order", ATTR_DESC(gate_order, AnyTraits<std::string>())},
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{"reset_after", ATTR_DESC(reset_after, AnyTraits<bool>())}};
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// 属性映射，列出了"direction"和"activation""gate_order"属性，类型为std::string
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//"cell_depth"和"num_proj",类型为int64_t
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//"reset_after""is_training"和"time_major"，类型为bool
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//"keep_prob""cell_clip"，类型为float
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OUTPUT_MAP(DynamicGRUV2Grad) = {{0, OUTPUT_DESC(dw_input)}, {1, OUTPUT_DESC(dw_hidden)}, {2, OUTPUT_DESC(db_input)},
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{3, OUTPUT_DESC(db_hidden)}, {4, OUTPUT_DESC(dx)}, {5, OUTPUT_DESC(dh_prev)}};
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// 输入映射，共六个，dw_input索引为0，dw_hidden索引为1，db_input索引为2，db_hidden索引为3，dx索引为4，dh_prev索引为5
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REG_ADPT_DESC(DynamicGRUV2Grad, kNameDynamicGRUV2Grad, ADPT_DESC(DynamicGRUV2Grad))
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// 注册DynamicGRUV2Grad操作的适配器描述kNameDynamicGRUV2Grad
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} // namespace mindspore::transform
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