From c8a676604b0ff18ff833274b38a0dd1cde00cf09 Mon Sep 17 00:00:00 2001
From: liyaguang <liyaguang0123@gmail.com>
Date: Tue, 8 Jan 2019 11:21:22 -0800
Subject: [PATCH] Add PEMS-BAY configuration.

---
 README.md                                     | 28 ++++++++-----
 data/model/dcrnn_bay.yaml                     | 39 +++++++++++++++++++
 .../{dcrnn_config.yaml => dcrnn_la.yaml}      |  0
 3 files changed, 58 insertions(+), 9 deletions(-)
 create mode 100644 data/model/dcrnn_bay.yaml
 rename data/model/{dcrnn_config.yaml => dcrnn_la.yaml} (100%)

diff --git a/README.md b/README.md
index 165a668..bc7060f 100644
--- a/README.md
+++ b/README.md
@@ -20,28 +20,38 @@ pip install -r requirements.txt
 ```
 
 ## Data Preparation
-The traffic data file for Los Angeles, i.e., `df_highway_2012_4mon_sample.h5`, is available at [Google Drive](https://drive.google.com/open?id=1tjf5aXCgUoimvADyxKqb-YUlxP8O46pb) or [Baidu Yun](https://pan.baidu.com/s/1rsCq38a9SRyFO1F68tUscA), and should be
-put into the `data/METR-LA` folder.
-Besides, the locations of sensors are available at [data/sensor_graph/graph_sensor_locations.csv](https://github.com/liyaguang/DCRNN/blob/master/data/sensor_graph/graph_sensor_locations.csv).
+The traffic data files for Los Angeles and the Bay Area, i.e., `metr-la.h5` and `pems-bay.h5`, are available at [Google Drive](https://drive.google.com/open?id=10FOTa6HXPqX8Pf5WRoRwcFnW9BrNZEIX) or [Baidu Yun](hbttps://pan.baidu.com/s/14Yy9isAIZYdU__OYEQGa_g), and should be
+put into the `data/` folder.
+Besides, the locations of sensors Los Angeles are available at [data/sensor_graph/graph_sensor_locations.csv](https://github.com/liyaguang/DCRNN/blob/master/data/sensor_graph/graph_sensor_locations.csv).
 ```bash
-python -m scripts.generate_training_data --output_dir=data/METR-LA
+mkdir -p data/{METR-LA,PEMS-BAY}
+
+# METR-LA
+python -m scripts.generate_training_data --output_dir=data/METR-LA --traffic_df_filename=data/metr-la.h5
+
+# PEMS-BAY
+python -m scripts.generate_training_data --output_dir=data/PEMS-BAY --traffic_df_filename=data/pems-bay.h5
 ```
-The generated train/val/test dataset will be saved at `data/METR-LA/{train,val,test}.npz`.
+The generated train/val/test dataset will be saved at `data/{METR-LA,PEMS-BAY}/{train,val,test}.npz`.
 
 
-## Run the Pre-trained Model
+## Run the Pre-trained Model on METR-LA
 
 ```bash
 python run_demo.py
 ```
-The generated prediction of DCRNN is in `data/results/dcrnn_predictions_[1-12].h5`.
+The generated prediction of DCRNN of METR-LA is in `data/results/dcrnn_predictions_[1-12].h5`.
 
 
 ## Model Training
 ```bash
-python dcrnn_train.py --config_filename=data/model/dcrnn_config.yaml
+# METR-LA
+python dcrnn_train.py --config_filename=data/model/dcrnn_la.yaml
+
+# PEMS-BAY
+python dcrnn_train.py --config_filename=data/model/dcrnn_bay.yaml
 ```
-Each epoch takes about 5min with a single GTX 1080 Ti.
+Each epoch takes about 5min or 10 min on a single GTX 1080 Ti for METR-LA or PEMS-BAY respectively.
 
 ## Graph Construction
  As the currently implementation is based on pre-calculated road network distances between sensors, it currently only
diff --git a/data/model/dcrnn_bay.yaml b/data/model/dcrnn_bay.yaml
new file mode 100644
index 0000000..31dec27
--- /dev/null
+++ b/data/model/dcrnn_bay.yaml
@@ -0,0 +1,39 @@
+---
+base_dir: data/model
+log_level: INFO
+data:
+  batch_size: 64
+  dataset_dir: data/PEMS-BAY
+  test_batch_size: 64
+  val_batch_size: 64
+  graph_pkl_filename: data/sensor_graph/adj_mx_bay.pkl
+
+model:
+  cl_decay_steps: 2000
+  filter_type: dual_random_walk
+  horizon: 12
+  input_dim: 2
+  l1_decay: 0
+  max_diffusion_step: 2
+  num_nodes: 325
+  num_rnn_layers: 2
+  output_dim: 1
+  rnn_units: 64 
+  seq_len: 12
+  use_curriculum_learning: true
+
+train:
+  base_lr: 0.01
+  dropout: 0
+  epoch: 0
+  epochs: 100
+  epsilon: 1.0e-3
+  global_step: 0
+  lr_decay_ratio: 0.1
+  max_grad_norm: 5
+  max_to_keep: 100
+  min_learning_rate: 2.0e-06
+  optimizer: adam
+  patience: 50
+  steps: [20, 30, 40, 50]
+  test_every_n_epochs: 10
diff --git a/data/model/dcrnn_config.yaml b/data/model/dcrnn_la.yaml
similarity index 100%
rename from data/model/dcrnn_config.yaml
rename to data/model/dcrnn_la.yaml