Dev pnn pr #340
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Dev pnn pr #340
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ShawnXuan
reviewed
May 23, 2022
| pnn_train_eval.py \ | ||
| --data_dir $DATA_DIR \ | ||
| --persistent_path $PERSISTENT_PATH \ | ||
| --table_size_array "43, 98, 121, 41, 219, 112, 79, 68, 91, 5, 26, 36, 70, 1447, 554, 157461, 117683, 305, 17, 11878, 629, 4, 39504, 5128, 156729, 3175, 27, 11070, 149083, 11, 4542, 1996, 4, 154737, 17, 16, 52989, 81, 40882" \ |
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ShawnXuan
reviewed
May 23, 2022
RecommenderSystems/pnn/train_pnn.sh
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| pnn_train_eval.py \ | ||
| --data_dir $DATA_DIR \ | ||
| --persistent_path $PERSISTENT_PATH \ | ||
| --table_size_array "43, 98, 121, 41, 219, 112, 79, 68, 91, 5, 26, 36, 70, 1447, 554, 157461, 117683, 305, 17, 11878, 629, 4, 39504, 5128, 156729, 3175, 27, 11070, 149083, 11, 4542, 1996, 4, 154737, 17, 16, 52989, 81, 40882" \ |
ShawnXuan
reviewed
May 23, 2022
| return self.one_embedding.forward(ids) | ||
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| class DenseLayer(nn.Module): |
ShawnXuan
reviewed
May 30, 2022
| one_embedding_store_type="cached_host_mem", | ||
| cache_memory_budget_mb=8192, | ||
| interaction_type="dot", | ||
| interaction_itself=False, |
ShawnXuan
reviewed
May 30, 2022
| self.input_dim = embedding_vec_size * self.fields | ||
| if self.use_inner: | ||
| self.input_dim += sum(range(self.fields)) | ||
| self.inner_product_layer = InnerProductLayer( |
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similar with
https://github.com/Oneflow-Inc/models/blob/main/RecommenderSystems/dlrm/dlrm_train_eval.py#L236
output_concat = None
ShawnXuan
requested changes
May 30, 2022
ShawnXuan
reviewed
May 30, 2022
| I = self.inner_product_layer(E) | ||
| if self.use_outter: | ||
| O = self.outter_product_layer( | ||
| E.reshape(self.fields, -1, 1, self.embedding_vec_size) |
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what is the purpose of reshape here???
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E的形状本来是（b, fields, embedding_vec_size）, reshape之后是（fields， b, 1, embedding_vec_size）。为了传入opnn网络进行训练。
ShawnXuan
requested changes
May 30, 2022
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