提交 adac28f2 编写于 作者: M malin10

update config.yaml

上级 150b2886
......@@ -12,60 +12,63 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# 轮数
epochs: 4
# 设备
device: cpu
# 工作目录
workspace: "paddlerec.models.match.dssm"
# dataset列表
dataset:
- name: dataset_train # 名字,用来区分不同的dataset
- name: dataset_train
batch_size: 4
type: QueueDataset
data_path: "{workspace}/data/train" # 数据路径
data_path: "{workspace}/data/train"
data_converter: "{workspace}/synthetic_reader.py"
#- name: dataset_infer # 名字,用来区分不同的dataset
# batch_size: 1
# type: QueueDataset
# data_path: "{workspace}/data/train" # 数据路径
# data_converter: "{workspace}/synthetic_evaluate_reader.py"
- name: dataset_infer
batch_size: 1
type: QueueDataset
data_path: "{workspace}/data/train"
data_converter: "{workspace}/synthetic_evaluate_reader.py"
# 超参数
hyper_parameters:
#优化器
optimizer:
class: sgd
learning_rate: 0.01
strategy: async
# 用户自定义
TRIGRAM_D: 1000
NEG: 4
fc_sizes: [300, 300, 128]
fc_acts: ['tanh', 'tanh', 'tanh']
# executor配置
epoch:
name:
trainer_class: single
save_checkpoint_interval: 2 # 保存模型
save_inference_interval: 4 # 保存预测模型
save_checkpoint_path: "increment" # 保存模型路径
save_inference_path: "inference" # 保存预测模型路径
save_inference_feed_varnames: ["query", "doc_pos"] # 预测模型feed vars
save_inference_fetch_varnames: ["cos_sim_0.tmp_0"] # 预测模型 fetch vars
#init_model_path: "xxxx" # 加载模型
mode: runner1
# config of each runner.
# runner is a kind of paddle training class, which wraps the train/infer process.
runner:
- name: runner1
class: single_train
# num of epochs
epochs: 4
# device to run training or infer
device: cpu
save_checkpoint_interval: 2 # save model interval of epochs
save_inference_interval: 4 # save inference
save_checkpoint_path: "increment" # save checkpoint path
save_inference_path: "inference" # save inference path
save_inference_feed_varnames: ["query", "doc_pos"] # feed vars of save inference
save_inference_fetch_varnames: ["cos_sim_0.tmp_0"] # fetch vars of save inference
init_model_path: "" # load model path
fetch_period: 10
- name: runner2
class: single_infer
# num of epochs
epochs: 1
# device to run training or infer
device: cpu
init_model_path: "increment/2" # load model path
# 执行器,每轮要跑的所有模型
executor:
- name: train
model: "{workspace}/model.py" # 模型路径
dataset_name: dataset_train # 名字,用来区分不同的阶段
thread_num: 1 # 线程数
is_infer: False # 是否是infer
# - name: infer
# model: "{workspace}/model.py" # 模型路径
# dataset_name: dataset_infer # 名字,用来区分不同的阶段
# thread_num: 1 # 线程数
# is_infer: True # 是否是infer
# runner will run all the phase in each epoch
phase:
- name: phase1
model: "{workspace}/model.py" # user-defined model
dataset_name: dataset_train # select dataset by name
thread_num: 1
#- name: phase2
# model: "{workspace}/model.py" # user-defined model
# dataset_name: dataset_infer # select dataset by name
# thread_num: 1
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