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benchmark_gpubox.yaml
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benchmark_gpubox.yaml
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# workspace
#workspace: "models/rank/dnn"
runner:
train_data_dir: "train_data"
train_reader_path: "criteo_reader" # importlib format
use_gpu: True
use_auc: True
train_batch_size: 2048
epochs: 3
print_interval: 10
model_save_path: "output_model_dnn_queue"
sync_mode: "gpubox"
thread_num: 30
reader_type: "InmemoryDataset" # DataLoader / QueueDataset / RecDataset / InmemoryDataset
pipe_command: "python models/rank/dnn/benchmark_reader.py"
dataset_debug: False
split_file_list: False
infer_batch_size: 2
infer_reader_path: "criteo_reader" # importlib format
test_data_dir: "data/sample_data/train"
infer_load_path: "output_model_dnn_queue"
infer_start_epoch: 0
infer_end_epoch: 3
# hyper parameters of user-defined network
hyper_parameters:
# optimizer config
optimizer:
class: Adam
learning_rate: 0.001
strategy: async
# user-defined <key, value> pairs
sparse_inputs_slots: 27
sparse_feature_number: 1024
sparse_feature_dim: 11
dense_input_dim: 13
fc_sizes: [512, 256, 128, 32]
distributed_embedding: 0