From bb5f3cb33d32f1c186d6aadc157a39b29b91cafe Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Tue, 1 Dec 2020 09:59:46 +0800
Subject: [PATCH 01/17] Fix and move to version 0.6.0

---
 examples/run_all_model.py | 4 ++--
 qlib/__init__.py          | 2 +-
 setup.py                  | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/examples/run_all_model.py b/examples/run_all_model.py
index 8843573ab..3d8628c4a 100644
--- a/examples/run_all_model.py
+++ b/examples/run_all_model.py
@@ -243,11 +243,11 @@ def run(times=1, models=None, exclude=False):
         execute(f"{python_path} -m pip install --upgrade cython")  # TODO: FIX ME!
         if fn == "TFT":
             execute(
-                f"cd {env_path} && {python_path} -m pip install --upgrade --force-reinstall --ignore-installed PyYAML -e git+https://github.com/you-n-g/qlib#egg=pyqlib"
+                f"cd {env_path} && {python_path} -m pip install --upgrade --force-reinstall --ignore-installed PyYAML -e git+https://github.com/microsoft/qlib#egg=pyqlib"
             )  # TODO: FIX ME!
         else:
             execute(
-                f"cd {env_path} && {python_path} -m pip install --upgrade --force-reinstall -e git+https://github.com/you-n-g/qlib#egg=pyqlib"
+                f"cd {env_path} && {python_path} -m pip install --upgrade --force-reinstall -e git+https://github.com/microsoft/qlib#egg=pyqlib"
             )  # TODO: FIX ME!
         sys.stderr.write("\n")
         # run workflow_by_config for multiple times
diff --git a/qlib/__init__.py b/qlib/__init__.py
index 2b8989303..73d985d04 100644
--- a/qlib/__init__.py
+++ b/qlib/__init__.py
@@ -2,7 +2,7 @@
 # Licensed under the MIT License.
 
 
-__version__ = "0.6.0.alpha"
+__version__ = "0.6.0"
 
 import os
 import re
diff --git a/setup.py b/setup.py
index 0696a766f..b7a37e028 100644
--- a/setup.py
+++ b/setup.py
@@ -12,7 +12,7 @@ from setuptools import find_packages, setup, Extension
 NAME = "pyqlib"
 DESCRIPTION = "A Quantitative-research Platform"
 REQUIRES_PYTHON = ">=3.5.0"
-VERSION = "0.6.0.alpha"
+VERSION = "0.6.0"
 
 # Detect Cython
 try:

From 77884db3a562a795d29e16e844c0c21fa17c26e2 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Tue, 1 Dec 2020 11:54:26 +0800
Subject: [PATCH 02/17] Fix and update run_all_model

---
 .../ALSTM/workflow_config_alstm.yaml          |  1 -
 .../benchmarks/GATs/workflow_config_gats.yaml |  1 -
 .../benchmarks/GRU/workflow_config_gru.yaml   |  1 -
 .../benchmarks/LSTM/workflow_config_lstm.yaml |  1 -
 .../benchmarks/SFM/workflow_config_sfm.yaml   |  1 -
 examples/run_all_model.py                     | 19 ++++++++++++++++---
 qlib/contrib/model/pytorch_alstm.py           |  7 ++++---
 qlib/contrib/model/pytorch_gats.py            |  9 ++++++---
 qlib/contrib/model/pytorch_gru.py             |  7 ++++---
 qlib/contrib/model/pytorch_lstm.py            |  7 ++++---
 qlib/contrib/model/pytorch_nn.py              |  7 ++++---
 qlib/contrib/model/pytorch_sfm.py             |  7 ++++---
 12 files changed, 42 insertions(+), 26 deletions(-)

diff --git a/examples/benchmarks/ALSTM/workflow_config_alstm.yaml b/examples/benchmarks/ALSTM/workflow_config_alstm.yaml
index 66367034d..37dceaacb 100644
--- a/examples/benchmarks/ALSTM/workflow_config_alstm.yaml
+++ b/examples/benchmarks/ALSTM/workflow_config_alstm.yaml
@@ -54,7 +54,6 @@ task:
             batch_size: 800
             metric: loss
             loss: mse
-            seed: 0
             GPU: 0
             rnn_type: GRU
     dataset:
diff --git a/examples/benchmarks/GATs/workflow_config_gats.yaml b/examples/benchmarks/GATs/workflow_config_gats.yaml
index a608a7e49..d4f2c3106 100644
--- a/examples/benchmarks/GATs/workflow_config_gats.yaml
+++ b/examples/benchmarks/GATs/workflow_config_gats.yaml
@@ -56,7 +56,6 @@ task:
             base_model: LSTM
             with_pretrain: True
             model_path: "benchmarks/LSTM/model_lstm_csi300.pkl"
-            seed: 0
             GPU: 0
     dataset:
         class: DatasetH
diff --git a/examples/benchmarks/GRU/workflow_config_gru.yaml b/examples/benchmarks/GRU/workflow_config_gru.yaml
index 381581a77..64ae3437c 100644
--- a/examples/benchmarks/GRU/workflow_config_gru.yaml
+++ b/examples/benchmarks/GRU/workflow_config_gru.yaml
@@ -54,7 +54,6 @@ task:
             batch_size: 800
             metric: loss
             loss: mse
-            seed: 0
             GPU: 0
     dataset:
         class: DatasetH
diff --git a/examples/benchmarks/LSTM/workflow_config_lstm.yaml b/examples/benchmarks/LSTM/workflow_config_lstm.yaml
index cb3b2a789..b857d97d4 100644
--- a/examples/benchmarks/LSTM/workflow_config_lstm.yaml
+++ b/examples/benchmarks/LSTM/workflow_config_lstm.yaml
@@ -54,7 +54,6 @@ task:
             batch_size: 800
             metric: loss
             loss: mse
-            seed: 0
             GPU: 0
     dataset:
         class: DatasetH
diff --git a/examples/benchmarks/SFM/workflow_config_sfm.yaml b/examples/benchmarks/SFM/workflow_config_sfm.yaml
index edf176e62..d0a95bfa5 100644
--- a/examples/benchmarks/SFM/workflow_config_sfm.yaml
+++ b/examples/benchmarks/SFM/workflow_config_sfm.yaml
@@ -58,7 +58,6 @@ task:
             loss: mse
             optimizer: adam
             GPU: 1
-            seed: 710
     dataset:
         class: DatasetH
         module_path: qlib.data.dataset
diff --git a/examples/run_all_model.py b/examples/run_all_model.py
index 3d8628c4a..6df0ff4bb 100644
--- a/examples/run_all_model.py
+++ b/examples/run_all_model.py
@@ -152,6 +152,10 @@ def get_all_results(folders) -> dict:
         result["annualized_return_with_cost"] = list()
         result["information_ratio_with_cost"] = list()
         result["max_drawdown_with_cost"] = list()
+        result["ic"] = list()
+        result["icir"] = list()
+        result["rank_ic"] = list()
+        result["rank_icir"] = list()
         for recorder_id in recorders:
             if recorders[recorder_id].status == "FINISHED":
                 recorder = R.get_recorder(recorder_id=recorder_id, experiment_name=fn)
@@ -159,19 +163,27 @@ def get_all_results(folders) -> dict:
                 result["annualized_return_with_cost"].append(metrics["excess_return_with_cost.annualized_return"])
                 result["information_ratio_with_cost"].append(metrics["excess_return_with_cost.information_ratio"])
                 result["max_drawdown_with_cost"].append(metrics["excess_return_with_cost.max_drawdown"])
+                result["ic"].append(metrics["IC"])
+                result["icir"].append(metrics["ICIR"])
+                result["rank_ic"].append(metrics["Rank IC"])
+                result["rank_icir"].append(metrics["Rank ICIR"])
         results[fn] = result
     return results
 
 
 # function to generate and save markdown table
 def gen_and_save_md_table(metrics):
-    table = "| Model Name | Annualized Return | Information Ratio | Max Drawdown |\n"
-    table += "|---|---|---|---|\n"
+    table = "| Model Name | Annualized Return | Information Ratio | Max Drawdown | IC | ICIR | Rank IC | Rank ICIR |\n"
+    table += "|---|---|---|---|---|---|---|---|\n"
     for fn in metrics:
         ar = metrics[fn]["annualized_return_with_cost"]
         ir = metrics[fn]["information_ratio_with_cost"]
         md = metrics[fn]["max_drawdown_with_cost"]
-        table += f"| {fn} | {ar[0]:9.4f}±{ar[1]:9.2f} | {ir[0]:9.4f}±{ir[1]:9.2f}| {md[0]:9.4f}±{md[1]:9.2f} |\n"
+        ic = metrics[fn]["ic"]
+        icir = metrics[fn]["icir"]
+        ric = metrics[fn]["rank_ic"]
+        ricir = metrics[fn]["rank_icir"]
+        table += f"| {fn} | {ar[0]:5.4f}±{ar[1]:2.2f} | {ir[0]:5.4f}±{ir[1]:2.2f}| {md[0]:5.4f}±{md[1]:2.2f} | {ic[0]:5.4f}±{ic[1]:2.2f} | {icir[0]:5.4f}±{icir[1]:2.2f}| {ric[0]:5.4f}±{ric[1]:2.2f} | {ricir[0]:5.4f}±{ricir[1]:2.2f} |\n"
     pprint(table)
     with open("table.md", "w") as f:
         f.write(table)
@@ -240,6 +252,7 @@ def run(times=1, models=None, exclude=False):
             sys.stderr.write("\n")
         # install qlib
         sys.stderr.write("Installing qlib...\n")
+        execute(f"{python_path} -m pip install --upgrade pip")  # TODO: FIX ME!
         execute(f"{python_path} -m pip install --upgrade cython")  # TODO: FIX ME!
         if fn == "TFT":
             execute(
diff --git a/qlib/contrib/model/pytorch_alstm.py b/qlib/contrib/model/pytorch_alstm.py
index ba75c70ca..d992ec52f 100644
--- a/qlib/contrib/model/pytorch_alstm.py
+++ b/qlib/contrib/model/pytorch_alstm.py
@@ -57,7 +57,7 @@ class ALSTM(Model):
         loss="mse",
         optimizer="adam",
         GPU="0",
-        seed=0,
+        seed=None,
         **kwargs
     ):
         # Set logger.
@@ -113,8 +113,9 @@ class ALSTM(Model):
             )
         )
 
-        np.random.seed(self.seed)
-        torch.manual_seed(self.seed)
+        if self.seed is not None:
+            np.random.seed(self.seed)
+            torch.manual_seed(self.seed)
 
         self.ALSTM_model = ALSTMModel(
             d_feat=self.d_feat,
diff --git a/qlib/contrib/model/pytorch_gats.py b/qlib/contrib/model/pytorch_gats.py
index 2e19c0542..83f2633c5 100644
--- a/qlib/contrib/model/pytorch_gats.py
+++ b/qlib/contrib/model/pytorch_gats.py
@@ -62,7 +62,7 @@ class GATs(Model):
         model_path=None,
         optimizer="adam",
         GPU="0",
-        seed=0,
+        seed=None,
         **kwargs
     ):
         # Set logger.
@@ -123,8 +123,11 @@ class GATs(Model):
                 seed,
             )
         )
-        np.random.seed(self.seed)
-        torch.manual_seed(self.seed)
+
+        if self.seed is not None:
+            np.random.seed(self.seed)
+            torch.manual_seed(self.seed)
+
         self.GAT_model = GATModel(
             d_feat=self.d_feat,
             hidden_size=self.hidden_size,
diff --git a/qlib/contrib/model/pytorch_gru.py b/qlib/contrib/model/pytorch_gru.py
index 4ef4e2553..1c24017fc 100755
--- a/qlib/contrib/model/pytorch_gru.py
+++ b/qlib/contrib/model/pytorch_gru.py
@@ -57,7 +57,7 @@ class GRU(Model):
         loss="mse",
         optimizer="adam",
         GPU="0",
-        seed=0,
+        seed=None,
         **kwargs
     ):
         # Set logger.
@@ -113,8 +113,9 @@ class GRU(Model):
             )
         )
 
-        np.random.seed(self.seed)
-        torch.manual_seed(self.seed)
+        if self.seed is not None:
+            np.random.seed(self.seed)
+            torch.manual_seed(self.seed)
 
         self.gru_model = GRUModel(
             d_feat=self.d_feat,
diff --git a/qlib/contrib/model/pytorch_lstm.py b/qlib/contrib/model/pytorch_lstm.py
index 59df51e42..81e803e96 100755
--- a/qlib/contrib/model/pytorch_lstm.py
+++ b/qlib/contrib/model/pytorch_lstm.py
@@ -57,7 +57,7 @@ class LSTM(Model):
         loss="mse",
         optimizer="adam",
         GPU="0",
-        seed=0,
+        seed=None,
         **kwargs
     ):
         # Set logger.
@@ -113,8 +113,9 @@ class LSTM(Model):
             )
         )
 
-        np.random.seed(self.seed)
-        torch.manual_seed(self.seed)
+        if self.seed is not None:
+            np.random.seed(self.seed)
+            torch.manual_seed(self.seed)
 
         self.lstm_model = LSTMModel(
             d_feat=self.d_feat,
diff --git a/qlib/contrib/model/pytorch_nn.py b/qlib/contrib/model/pytorch_nn.py
index a60227ff0..fac9d4607 100644
--- a/qlib/contrib/model/pytorch_nn.py
+++ b/qlib/contrib/model/pytorch_nn.py
@@ -61,7 +61,7 @@ class DNNModelPytorch(Model):
         optimizer="gd",
         loss="mse",
         GPU="0",
-        seed=0,
+        seed=None,
         **kwargs
     ):
         # Set logger.
@@ -116,8 +116,9 @@ class DNNModelPytorch(Model):
             )
         )
 
-        np.random.seed(self.seed)
-        torch.manual_seed(self.seed)
+        if self.seed is not None:
+            np.random.seed(self.seed)
+            torch.manual_seed(self.seed)
 
         if loss not in {"mse", "binary"}:
             raise NotImplementedError("loss {} is not supported!".format(loss))
diff --git a/qlib/contrib/model/pytorch_sfm.py b/qlib/contrib/model/pytorch_sfm.py
index d845f6245..da75b1bca 100644
--- a/qlib/contrib/model/pytorch_sfm.py
+++ b/qlib/contrib/model/pytorch_sfm.py
@@ -217,7 +217,7 @@ class SFM(Model):
         loss="mse",
         optimizer="gd",
         GPU="0",
-        seed=0,
+        seed=None,
         **kwargs
     ):
         # Set logger.
@@ -282,8 +282,9 @@ class SFM(Model):
             )
         )
 
-        np.random.seed(self.seed)
-        torch.manual_seed(self.seed)
+        if self.seed is not None:
+            np.random.seed(self.seed)
+            torch.manual_seed(self.seed)
 
         self.sfm_model = SFM_Model(
             d_feat=self.d_feat,

From a2603fe27ad06acb5863987b4876f25951253412 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Wed, 2 Dec 2020 09:41:24 +0800
Subject: [PATCH 03/17] Update config

---
 examples/benchmarks/GATs/workflow_config_gats.yaml | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/examples/benchmarks/GATs/workflow_config_gats.yaml b/examples/benchmarks/GATs/workflow_config_gats.yaml
index d4f2c3106..0ab0cae8d 100644
--- a/examples/benchmarks/GATs/workflow_config_gats.yaml
+++ b/examples/benchmarks/GATs/workflow_config_gats.yaml
@@ -73,6 +73,11 @@ task:
         - class: SignalRecord
           module_path: qlib.workflow.record_temp
           kwargs: {}
+        - class: SigAnaRecord
+          module_path: qlib.workflow.record_temp
+          kwargs: 
+            ana_long_short: False
+            ann_scaler: 252
         - class: PortAnaRecord
           module_path: qlib.workflow.record_temp
           kwargs: 

From d109d3d44e88b4675b1289406c7d837aa88bb410 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Wed, 2 Dec 2020 12:23:42 +0800
Subject: [PATCH 04/17] Fix GPU

---
 examples/benchmarks/SFM/workflow_config_sfm.yaml | 2 +-
 qlib/contrib/model/pytorch_alstm.py              | 2 +-
 qlib/contrib/model/pytorch_gats.py               | 2 +-
 qlib/contrib/model/pytorch_gru.py                | 2 +-
 qlib/contrib/model/pytorch_lstm.py               | 2 +-
 qlib/contrib/model/pytorch_nn.py                 | 2 +-
 6 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/examples/benchmarks/SFM/workflow_config_sfm.yaml b/examples/benchmarks/SFM/workflow_config_sfm.yaml
index d0a95bfa5..5a0448cfe 100644
--- a/examples/benchmarks/SFM/workflow_config_sfm.yaml
+++ b/examples/benchmarks/SFM/workflow_config_sfm.yaml
@@ -57,7 +57,7 @@ task:
             eval_steps: 5
             loss: mse
             optimizer: adam
-            GPU: 1
+            GPU: 0
     dataset:
         class: DatasetH
         module_path: qlib.data.dataset
diff --git a/qlib/contrib/model/pytorch_alstm.py b/qlib/contrib/model/pytorch_alstm.py
index d992ec52f..9b5db8042 100644
--- a/qlib/contrib/model/pytorch_alstm.py
+++ b/qlib/contrib/model/pytorch_alstm.py
@@ -135,7 +135,7 @@ class ALSTM(Model):
             self.ALSTM_model.cuda()
             # set the visible GPU
             if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = self.visible_GPU
+                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
 
     def mse(self, pred, label):
         loss = (pred - label) ** 2
diff --git a/qlib/contrib/model/pytorch_gats.py b/qlib/contrib/model/pytorch_gats.py
index 83f2633c5..5bc91eb3b 100644
--- a/qlib/contrib/model/pytorch_gats.py
+++ b/qlib/contrib/model/pytorch_gats.py
@@ -147,7 +147,7 @@ class GATs(Model):
             self.GAT_model.cuda()
             # set the visible GPU
             if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = self.visible_GPU
+                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
 
     def mse(self, pred, label):
         loss = (pred - label) ** 2
diff --git a/qlib/contrib/model/pytorch_gru.py b/qlib/contrib/model/pytorch_gru.py
index 1c24017fc..7974e7c33 100755
--- a/qlib/contrib/model/pytorch_gru.py
+++ b/qlib/contrib/model/pytorch_gru.py
@@ -135,7 +135,7 @@ class GRU(Model):
             self.gru_model.cuda()
             # set the visible GPU
             if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = self.visible_GPU
+                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
 
     def mse(self, pred, label):
         loss = (pred - label) ** 2
diff --git a/qlib/contrib/model/pytorch_lstm.py b/qlib/contrib/model/pytorch_lstm.py
index 81e803e96..2eb6ae69f 100755
--- a/qlib/contrib/model/pytorch_lstm.py
+++ b/qlib/contrib/model/pytorch_lstm.py
@@ -135,7 +135,7 @@ class LSTM(Model):
             self.lstm_model.cuda()
             # set the visible GPU
             if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = self.visible_GPU
+                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
 
     def mse(self, pred, label):
         loss = (pred - label) ** 2
diff --git a/qlib/contrib/model/pytorch_nn.py b/qlib/contrib/model/pytorch_nn.py
index fac9d4607..a9d8a38d0 100644
--- a/qlib/contrib/model/pytorch_nn.py
+++ b/qlib/contrib/model/pytorch_nn.py
@@ -151,7 +151,7 @@ class DNNModelPytorch(Model):
             self.dnn_model.cuda()
             # set the visible GPU
             if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = self.visible_GPU
+                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
 
     def fit(
         self,

From 7f385345bb41d4af7dc6c27265ddc52d3cc8b633 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Wed, 2 Dec 2020 13:25:29 +0800
Subject: [PATCH 05/17] Fix GPU

---
 qlib/contrib/model/pytorch_alstm.py | 29 ++++++-------------------
 qlib/contrib/model/pytorch_gats.py  | 29 ++++++-------------------
 qlib/contrib/model/pytorch_gru.py   | 29 ++++++-------------------
 qlib/contrib/model/pytorch_lstm.py  | 29 ++++++-------------------
 qlib/contrib/model/pytorch_nn.py    | 33 ++++++++---------------------
 5 files changed, 37 insertions(+), 112 deletions(-)

diff --git a/qlib/contrib/model/pytorch_alstm.py b/qlib/contrib/model/pytorch_alstm.py
index 9b5db8042..cfe629fa8 100644
--- a/qlib/contrib/model/pytorch_alstm.py
+++ b/qlib/contrib/model/pytorch_alstm.py
@@ -76,7 +76,7 @@ class ALSTM(Model):
         self.early_stop = early_stop
         self.optimizer = optimizer.lower()
         self.loss = loss
-        self.visible_GPU = GPU
+        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
 
@@ -131,11 +131,7 @@ class ALSTM(Model):
             raise NotImplementedError("optimizer {} is not supported!".format(optimizer))
 
         self._fitted = False
-        if self.use_gpu:
-            self.ALSTM_model.cuda()
-            # set the visible GPU
-            if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
+        self.ALSTM_model.to(self.device)
 
     def mse(self, pred, label):
         loss = (pred - label) ** 2
@@ -173,12 +169,8 @@ class ALSTM(Model):
             if len(indices) - i < self.batch_size:
                 break
 
-            feature = torch.from_numpy(x_train_values[indices[i : i + self.batch_size]]).float()
-            label = torch.from_numpy(y_train_values[indices[i : i + self.batch_size]]).float()
-
-            if self.use_gpu:
-                feature = feature.cuda()
-                label = label.cuda()
+            feature = torch.from_numpy(x_train_values[indices[i : i + self.batch_size]]).float().to(self.device)
+            label = torch.from_numpy(y_train_values[indices[i : i + self.batch_size]]).float().to(self.device)
 
             pred = self.ALSTM_model(feature)
             loss = self.loss_fn(pred, label)
@@ -206,12 +198,8 @@ class ALSTM(Model):
             if len(indices) - i < self.batch_size:
                 break
 
-            feature = torch.from_numpy(x_values[indices[i : i + self.batch_size]]).float()
-            label = torch.from_numpy(y_values[indices[i : i + self.batch_size]]).float()
-
-            if self.use_gpu:
-                feature = feature.cuda()
-                label = label.cuda()
+            feature = torch.from_numpy(x_values[indices[i : i + self.batch_size]]).float().to(self.device)
+            label = torch.from_numpy(y_values[indices[i : i + self.batch_size]]).float().to(self.device)
 
             pred = self.ALSTM_model(feature)
             loss = self.loss_fn(pred, label)
@@ -299,10 +287,7 @@ class ALSTM(Model):
             else:
                 end = begin + self.batch_size
 
-            x_batch = torch.from_numpy(x_values[begin:end]).float()
-
-            if self.use_gpu:
-                x_batch = x_batch.cuda()
+            x_batch = torch.from_numpy(x_values[begin:end]).float().to(self.device)
 
             with torch.no_grad():
                 if self.use_gpu:
diff --git a/qlib/contrib/model/pytorch_gats.py b/qlib/contrib/model/pytorch_gats.py
index 5bc91eb3b..1759ae5ba 100644
--- a/qlib/contrib/model/pytorch_gats.py
+++ b/qlib/contrib/model/pytorch_gats.py
@@ -83,7 +83,7 @@ class GATs(Model):
         self.base_model = base_model
         self.with_pretrain = with_pretrain
         self.model_path = model_path
-        self.visible_GPU = GPU
+        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
 
@@ -143,11 +143,7 @@ class GATs(Model):
             raise NotImplementedError("optimizer {} is not supported!".format(optimizer))
 
         self._fitted = False
-        if self.use_gpu:
-            self.GAT_model.cuda()
-            # set the visible GPU
-            if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
+        self.GAT_model.to(self.device)
 
     def mse(self, pred, label):
         loss = (pred - label) ** 2
@@ -193,12 +189,8 @@ class GATs(Model):
 
         for idx, count in zip(daily_index, daily_count):
             batch = slice(idx, idx + count)
-            feature = torch.from_numpy(x_train_values[batch]).float()
-            label = torch.from_numpy(y_train_values[batch]).float()
-
-            if self.use_gpu:
-                feature = feature.cuda()
-                label = label.cuda()
+            feature = torch.from_numpy(x_train_values[batch]).float().to(self.device)
+            label = torch.from_numpy(y_train_values[batch]).float().to(self.device)
 
             pred = self.GAT_model(feature)
             loss = self.loss_fn(pred, label)
@@ -224,12 +216,8 @@ class GATs(Model):
 
         for idx, count in zip(daily_index, daily_count):
             batch = slice(idx, idx + count)
-            feature = torch.from_numpy(x_values[batch]).float()
-            label = torch.from_numpy(y_values[batch]).float()
-
-            if self.use_gpu:
-                feature = feature.cuda()
-                label = label.cuda()
+            feature = torch.from_numpy(x_values[batch]).float().to(self.device)
+            label = torch.from_numpy(y_values[batch]).float().to(self.device)
 
             pred = self.GAT_model(feature)
             loss = self.loss_fn(pred, label)
@@ -333,10 +321,7 @@ class GATs(Model):
 
         for idx, count in zip(daily_index, daily_count):
             batch = slice(idx, idx + count)
-            x_batch = torch.from_numpy(x_values[batch]).float()
-
-            if self.use_gpu:
-                x_batch = x_batch.cuda()
+            x_batch = torch.from_numpy(x_values[batch]).float().to(self.device)
 
             with torch.no_grad():
                 if self.use_gpu:
diff --git a/qlib/contrib/model/pytorch_gru.py b/qlib/contrib/model/pytorch_gru.py
index 7974e7c33..8d5a9e461 100755
--- a/qlib/contrib/model/pytorch_gru.py
+++ b/qlib/contrib/model/pytorch_gru.py
@@ -76,7 +76,7 @@ class GRU(Model):
         self.early_stop = early_stop
         self.optimizer = optimizer.lower()
         self.loss = loss
-        self.visible_GPU = GPU
+        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
 
@@ -131,11 +131,7 @@ class GRU(Model):
             raise NotImplementedError("optimizer {} is not supported!".format(optimizer))
 
         self._fitted = False
-        if self.use_gpu:
-            self.gru_model.cuda()
-            # set the visible GPU
-            if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
+        self.gru_model.to(self.device)
 
     def mse(self, pred, label):
         loss = (pred - label) ** 2
@@ -173,12 +169,8 @@ class GRU(Model):
             if len(indices) - i < self.batch_size:
                 break
 
-            feature = torch.from_numpy(x_train_values[indices[i : i + self.batch_size]]).float()
-            label = torch.from_numpy(y_train_values[indices[i : i + self.batch_size]]).float()
-
-            if self.use_gpu:
-                feature = feature.cuda()
-                label = label.cuda()
+            feature = torch.from_numpy(x_train_values[indices[i : i + self.batch_size]]).float().to(self.device)
+            label = torch.from_numpy(y_train_values[indices[i : i + self.batch_size]]).float().to(self.device)
 
             pred = self.gru_model(feature)
             loss = self.loss_fn(pred, label)
@@ -206,12 +198,8 @@ class GRU(Model):
             if len(indices) - i < self.batch_size:
                 break
 
-            feature = torch.from_numpy(x_values[indices[i : i + self.batch_size]]).float()
-            label = torch.from_numpy(y_values[indices[i : i + self.batch_size]]).float()
-
-            if self.use_gpu:
-                feature = feature.cuda()
-                label = label.cuda()
+            feature = torch.from_numpy(x_values[indices[i : i + self.batch_size]]).float().to(self.device)
+            label = torch.from_numpy(y_values[indices[i : i + self.batch_size]]).float().to(self.device)
 
             pred = self.gru_model(feature)
             loss = self.loss_fn(pred, label)
@@ -299,10 +287,7 @@ class GRU(Model):
             else:
                 end = begin + self.batch_size
 
-            x_batch = torch.from_numpy(x_values[begin:end]).float()
-
-            if self.use_gpu:
-                x_batch = x_batch.cuda()
+            x_batch = torch.from_numpy(x_values[begin:end]).float().to(self.device)
 
             with torch.no_grad():
                 if self.use_gpu:
diff --git a/qlib/contrib/model/pytorch_lstm.py b/qlib/contrib/model/pytorch_lstm.py
index 2eb6ae69f..8032c54eb 100755
--- a/qlib/contrib/model/pytorch_lstm.py
+++ b/qlib/contrib/model/pytorch_lstm.py
@@ -76,7 +76,7 @@ class LSTM(Model):
         self.early_stop = early_stop
         self.optimizer = optimizer.lower()
         self.loss = loss
-        self.visible_GPU = GPU
+        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
 
@@ -131,11 +131,7 @@ class LSTM(Model):
             raise NotImplementedError("optimizer {} is not supported!".format(optimizer))
 
         self._fitted = False
-        if self.use_gpu:
-            self.lstm_model.cuda()
-            # set the visible GPU
-            if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
+        self.lstm_model.to(self.device)
 
     def mse(self, pred, label):
         loss = (pred - label) ** 2
@@ -173,12 +169,8 @@ class LSTM(Model):
             if len(indices) - i < self.batch_size:
                 break
 
-            feature = torch.from_numpy(x_train_values[indices[i : i + self.batch_size]]).float()
-            label = torch.from_numpy(y_train_values[indices[i : i + self.batch_size]]).float()
-
-            if self.use_gpu:
-                feature = feature.cuda()
-                label = label.cuda()
+            feature = torch.from_numpy(x_train_values[indices[i : i + self.batch_size]]).float().to(self.device)
+            label = torch.from_numpy(y_train_values[indices[i : i + self.batch_size]]).float().to(self.device)
 
             pred = self.lstm_model(feature)
             loss = self.loss_fn(pred, label)
@@ -206,12 +198,8 @@ class LSTM(Model):
             if len(indices) - i < self.batch_size:
                 break
 
-            feature = torch.from_numpy(x_values[indices[i : i + self.batch_size]]).float()
-            label = torch.from_numpy(y_values[indices[i : i + self.batch_size]]).float()
-
-            if self.use_gpu:
-                feature = feature.cuda()
-                label = label.cuda()
+            feature = torch.from_numpy(x_values[indices[i : i + self.batch_size]]).float().to(self.device)
+            label = torch.from_numpy(y_values[indices[i : i + self.batch_size]]).float().to(self.device)
 
             pred = self.lstm_model(feature)
             loss = self.loss_fn(pred, label)
@@ -299,10 +287,7 @@ class LSTM(Model):
             else:
                 end = begin + self.batch_size
 
-            x_batch = torch.from_numpy(x_values[begin:end]).float()
-
-            if self.use_gpu:
-                x_batch = x_batch.cuda()
+            x_batch = torch.from_numpy(x_values[begin:end]).float().to(self.device)
 
             with torch.no_grad():
                 if self.use_gpu:
diff --git a/qlib/contrib/model/pytorch_nn.py b/qlib/contrib/model/pytorch_nn.py
index a9d8a38d0..ed4ba8692 100644
--- a/qlib/contrib/model/pytorch_nn.py
+++ b/qlib/contrib/model/pytorch_nn.py
@@ -79,7 +79,7 @@ class DNNModelPytorch(Model):
         self.lr_decay_steps = lr_decay_steps
         self.optimizer = optimizer.lower()
         self.loss_type = loss
-        self.visible_GPU = GPU
+        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
         self.use_GPU = torch.cuda.is_available()
         self.seed = seed
 
@@ -147,11 +147,7 @@ class DNNModelPytorch(Model):
         )
 
         self._fitted = False
-        if self.use_GPU:
-            self.dnn_model.cuda()
-            # set the visible GPU
-            if self.visible_GPU:
-                os.environ["CUDA_VISIBLE_DEVICES"] = str(self.visible_GPU)
+        self.dnn_model.to(self.device)
 
     def fit(
         self,
@@ -188,13 +184,9 @@ class DNNModelPytorch(Model):
         w_train_values = torch.from_numpy(w_train.values).float()
         train_num = y_train_values.shape[0]
         # prepare validation data
-        x_val_auto = torch.from_numpy(x_valid.values).float()
-        y_val_auto = torch.from_numpy(y_valid.values).float()
-        w_val_auto = torch.from_numpy(w_valid.values).float()
-        if self.use_GPU:
-            x_val_auto = x_val_auto.cuda()
-            y_val_auto = y_val_auto.cuda()
-            w_val_auto = w_val_auto.cuda()
+        x_val_auto = torch.from_numpy(x_valid.values).float().to(self.device)
+        y_val_auto = torch.from_numpy(y_valid.values).float().to(self.device)
+        w_val_auto = torch.from_numpy(w_valid.values).float().to(self.device)
 
         for step in range(self.max_steps):
             if stop_steps >= self.early_stop_rounds:
@@ -205,14 +197,9 @@ class DNNModelPytorch(Model):
             self.dnn_model.train()
             self.train_optimizer.zero_grad()
             choice = np.random.choice(train_num, self.batch_size)
-            x_batch_auto = x_train_values[choice]
-            y_batch_auto = y_train_values[choice]
-            w_batch_auto = w_train_values[choice]
-
-            if self.use_GPU:
-                x_batch_auto = x_batch_auto.cuda()
-                y_batch_auto = y_batch_auto.cuda()
-                w_batch_auto = w_batch_auto.cuda()
+            x_batch_auto = x_train_values[choice].to(self.device)
+            y_batch_auto = y_train_values[choice].to(self.device)
+            w_batch_auto = w_train_values[choice].to(self.device)
 
             # forward
             preds = self.dnn_model(x_batch_auto)
@@ -277,9 +264,7 @@ class DNNModelPytorch(Model):
         if not self._fitted:
             raise ValueError("model is not fitted yet!")
         x_test_pd = dataset.prepare("test", col_set="feature")
-        x_test = torch.from_numpy(x_test_pd.values).float()
-        if self.use_GPU:
-            x_test = x_test.cuda()
+        x_test = torch.from_numpy(x_test_pd.values).float().to(self.device)
         self.dnn_model.eval()
 
         with torch.no_grad():

From 745b93138d300e1e4ff90b6b79f193b2c18fe5b4 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Wed, 2 Dec 2020 13:28:32 +0800
Subject: [PATCH 06/17] Update devices

---
 qlib/contrib/model/pytorch_alstm.py | 2 +-
 qlib/contrib/model/pytorch_gats.py  | 2 +-
 qlib/contrib/model/pytorch_gru.py   | 2 +-
 qlib/contrib/model/pytorch_lstm.py  | 2 +-
 qlib/contrib/model/pytorch_nn.py    | 2 +-
 qlib/contrib/model/pytorch_sfm.py   | 2 +-
 6 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/qlib/contrib/model/pytorch_alstm.py b/qlib/contrib/model/pytorch_alstm.py
index cfe629fa8..d85fef628 100644
--- a/qlib/contrib/model/pytorch_alstm.py
+++ b/qlib/contrib/model/pytorch_alstm.py
@@ -76,7 +76,7 @@ class ALSTM(Model):
         self.early_stop = early_stop
         self.optimizer = optimizer.lower()
         self.loss = loss
-        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
+        self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu")
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
 
diff --git a/qlib/contrib/model/pytorch_gats.py b/qlib/contrib/model/pytorch_gats.py
index 1759ae5ba..c22e48204 100644
--- a/qlib/contrib/model/pytorch_gats.py
+++ b/qlib/contrib/model/pytorch_gats.py
@@ -83,7 +83,7 @@ class GATs(Model):
         self.base_model = base_model
         self.with_pretrain = with_pretrain
         self.model_path = model_path
-        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
+        self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu")
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
 
diff --git a/qlib/contrib/model/pytorch_gru.py b/qlib/contrib/model/pytorch_gru.py
index 8d5a9e461..22c63c539 100755
--- a/qlib/contrib/model/pytorch_gru.py
+++ b/qlib/contrib/model/pytorch_gru.py
@@ -76,7 +76,7 @@ class GRU(Model):
         self.early_stop = early_stop
         self.optimizer = optimizer.lower()
         self.loss = loss
-        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
+        self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu")
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
 
diff --git a/qlib/contrib/model/pytorch_lstm.py b/qlib/contrib/model/pytorch_lstm.py
index 8032c54eb..1c24246f8 100755
--- a/qlib/contrib/model/pytorch_lstm.py
+++ b/qlib/contrib/model/pytorch_lstm.py
@@ -76,7 +76,7 @@ class LSTM(Model):
         self.early_stop = early_stop
         self.optimizer = optimizer.lower()
         self.loss = loss
-        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
+        self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu")
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
 
diff --git a/qlib/contrib/model/pytorch_nn.py b/qlib/contrib/model/pytorch_nn.py
index ed4ba8692..2e2a3e885 100644
--- a/qlib/contrib/model/pytorch_nn.py
+++ b/qlib/contrib/model/pytorch_nn.py
@@ -79,7 +79,7 @@ class DNNModelPytorch(Model):
         self.lr_decay_steps = lr_decay_steps
         self.optimizer = optimizer.lower()
         self.loss_type = loss
-        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
+        self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu")
         self.use_GPU = torch.cuda.is_available()
         self.seed = seed
 
diff --git a/qlib/contrib/model/pytorch_sfm.py b/qlib/contrib/model/pytorch_sfm.py
index da75b1bca..15d945c89 100644
--- a/qlib/contrib/model/pytorch_sfm.py
+++ b/qlib/contrib/model/pytorch_sfm.py
@@ -239,7 +239,7 @@ class SFM(Model):
         self.eval_steps = eval_steps
         self.optimizer = optimizer.lower()
         self.loss = loss
-        self.device = "cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu"
+        self.device = torch.device("cuda:%d" % (GPU) if torch.cuda.is_available() else "cpu")
         self.use_gpu = torch.cuda.is_available()
         self.seed = seed
 

From 91c3dfddf51bd169cf57ebd40b2162a1c9156b59 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Wed, 2 Dec 2020 17:55:11 +0800
Subject: [PATCH 07/17] Update run_all_model

---
 examples/run_all_model.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/examples/run_all_model.py b/examples/run_all_model.py
index 6df0ff4bb..78e01f623 100644
--- a/examples/run_all_model.py
+++ b/examples/run_all_model.py
@@ -15,6 +15,7 @@ import traceback
 import functools
 import statistics
 import subprocess
+from datetime import datetime
 from pathlib import Path
 from operator import xor
 from pprint import pprint
@@ -45,8 +46,6 @@ if not exists_qlib_data(provider_uri):
 
     GetData().qlib_data(target_dir=provider_uri, region=REG_CN)
 qlib.init(provider_uri=provider_uri, region=REG_CN, exp_manager=exp_manager)
-if os.path.isdir(exp_path):
-    shutil.rmtree(exp_path)
 
 # decorator to check the arguments
 def only_allow_defined_args(function_to_decorate):
@@ -291,7 +290,8 @@ def run(times=1, models=None, exclude=False):
     sys.stderr.write(f"Here are some of the errors of the models...\n")
     pprint(errors)
     sys.stderr.write("\n")
-
+    # move results folder
+    shutil.move(exp_path, exp_path + f"_{datetime.now().strftime("%Y-%m-%d_%H:%M:%S")}")
 
 if __name__ == "__main__":
     fire.Fire(run)  # run all the model

From 703ae5d4aab1d52b074cc05c691a439253445525 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Wed, 2 Dec 2020 18:00:26 +0800
Subject: [PATCH 08/17] Update tft and readme

---
 README.md                                                | 6 +++---
 examples/benchmarks/TFT/data_formatters/qlib_Alpha158.py | 2 +-
 examples/run_all_model.py                                | 3 ++-
 3 files changed, 6 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index b1a5f7092..1999160a1 100644
--- a/README.md
+++ b/README.md
@@ -27,10 +27,10 @@ For more details, please refer to our paper ["Qlib: An AI-oriented Quantitative
   - [Data Preparation](#data-preparation)
   - [Auto Quant Research Workflow](#auto-quant-research-workflow)
   - [Building Customized Quant Research Workflow by Code](#building-customized-quant-research-workflow-by-code)
-- [**Quant Model Zoo**](#quant-model-zoo)
+- [Quant Model Zoo](#quant-model-zoo)
   - [Run a single model](#run-a-single-model)
   - [Run multiple models](#run-multiple-models)
-- [**Quant Dataset Zoo**](#quant-dataset-zoo)
+- [Quant Dataset Zoo](#quant-dataset-zoo)
 - [More About Qlib](#more-about-qlib)
 - [Offline Mode and Online Mode](#offline-mode-and-online-mode)
   - [Performance of Qlib Data Server](#performance-of-qlib-data-server)
@@ -218,7 +218,7 @@ All the models listed above are runnable with ``Qlib``. Users can find the confi
 ## Run multiple models
 `Qlib` also provides a script [`run_all_model.py`](examples/run_all_model.py) which can run multiple models for several iterations. (**Note**: the script only supprots *Linux* now. Other OS will be supported in the future.)
 
-The script will create a unique virtual environment for each model, and delete the environments after training. Thus, only experiment results such as `IC` and `backtest` results will be generated and stored. (**Note**: the script will erase your previous experiment records created by running itself.)
+The script will create a unique virtual environment for each model, and delete the environments after training. Thus, only experiment results such as `IC` and `backtest` results will be generated and stored.
 
 Here is an example of running all the models for 10 iterations:
 ```python
diff --git a/examples/benchmarks/TFT/data_formatters/qlib_Alpha158.py b/examples/benchmarks/TFT/data_formatters/qlib_Alpha158.py
index 44a9284f7..03c169b9b 100644
--- a/examples/benchmarks/TFT/data_formatters/qlib_Alpha158.py
+++ b/examples/benchmarks/TFT/data_formatters/qlib_Alpha158.py
@@ -208,7 +208,7 @@ class Alpha158Formatter(GenericDataFormatter):
 
         model_params = {
             "dropout_rate": 0.4,
-            "hidden_layer_size": 16,
+            "hidden_layer_size": 160,
             "learning_rate": 0.0001,
             "minibatch_size": 128,
             "max_gradient_norm": 0.0135,
diff --git a/examples/run_all_model.py b/examples/run_all_model.py
index 78e01f623..416f1b47f 100644
--- a/examples/run_all_model.py
+++ b/examples/run_all_model.py
@@ -291,7 +291,8 @@ def run(times=1, models=None, exclude=False):
     pprint(errors)
     sys.stderr.write("\n")
     # move results folder
-    shutil.move(exp_path, exp_path + f"_{datetime.now().strftime("%Y-%m-%d_%H:%M:%S")}")
+    shutil.move(exp_path, exp_path + f"_{datetime.now().strftime('%Y-%m-%d_%H:%M:%S')}")
+
 
 if __name__ == "__main__":
     fire.Fire(run)  # run all the model

From ab762b3cd79ba9c08cc97b7279f32f88e6557dcb Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Wed, 2 Dec 2020 20:04:00 +0800
Subject: [PATCH 09/17] Update lightgbm lr

---
 examples/benchmarks/LightGBM/workflow_config_lightgbm.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/benchmarks/LightGBM/workflow_config_lightgbm.yaml b/examples/benchmarks/LightGBM/workflow_config_lightgbm.yaml
index 76a6347db..88202be1b 100644
--- a/examples/benchmarks/LightGBM/workflow_config_lightgbm.yaml
+++ b/examples/benchmarks/LightGBM/workflow_config_lightgbm.yaml
@@ -32,7 +32,7 @@ task:
         kwargs:
             loss: mse
             colsample_bytree: 0.8879
-            learning_rate: 0.0421
+            learning_rate: 0.2
             subsample: 0.8789
             lambda_l1: 205.6999
             lambda_l2: 580.9768

From f237a344c34e7e7a27735c4754c9a0589947dbd9 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Fri, 4 Dec 2020 10:31:50 +0800
Subject: [PATCH 10/17] Update

---
 examples/run_all_model.py | 26 ++++++++++++++++----------
 qlib/__init__.py          |  2 +-
 requirements.txt          | 25 -------------------------
 setup.py                  |  2 +-
 4 files changed, 18 insertions(+), 37 deletions(-)
 delete mode 100644 requirements.txt

diff --git a/examples/run_all_model.py b/examples/run_all_model.py
index 416f1b47f..9cc1bd2d6 100644
--- a/examples/run_all_model.py
+++ b/examples/run_all_model.py
@@ -135,9 +135,9 @@ def get_all_folders(models, exclude) -> dict:
 
 
 # function to get all the files under the model folder
-def get_all_files(folder_path) -> (str, str):
-    yaml_path = str(Path(f"{folder_path}") / "*.yaml")
-    req_path = str(Path(f"{folder_path}") / "*.txt")
+def get_all_files(folder_path, dataset) -> (str, str):
+    yaml_path = str(Path(f"{folder_path}") / f"*{dataset}*.yaml")
+    req_path = str(Path(f"{folder_path}") / f"*{dataset}*.txt")
     return glob.glob(yaml_path)[0], glob.glob(req_path)[0]
 
 
@@ -191,7 +191,7 @@ def gen_and_save_md_table(metrics):
 
 # function to run the all the models
 @only_allow_defined_args
-def run(times=1, models=None, exclude=False):
+def run(times=1, models=None, dataset='Alpha360', exclude=False):
     """
     Please be aware that this function can only work under Linux. MacOS and Windows will be supported in the future.
     Any PR to enhance this method is highly welcomed.
@@ -204,6 +204,8 @@ def run(times=1, models=None, exclude=False):
         determines the specific model or list of models to run or exclude.
     exclude : boolean
         determines whether the model being used is excluded or included.
+    dataset : str
+        determines the dataset to be used for each model.
 
     Usage:
     -------
@@ -217,13 +219,16 @@ def run(times=1, models=None, exclude=False):
         # Case 2 - run specific models multiple times
         python run_all_model.py 3 mlp
 
-        # Case 3 - run other models except those are given as arguments for multiple times
-        python run_all_model.py 3 [mlp,tft,lstm] True
+        # Case 3 - run specific models multiple times with specific dataset
+        python run_all_model.py 3 mlp Alpha158
 
-        # Case 4 - run specific models for one time
+        # Case 4 - run other models except those are given as arguments for multiple times
+        python run_all_model.py 3 [mlp,tft,lstm] --exclude=True
+
+        # Case 5 - run specific models for one time
         python run_all_model.py --models=[mlp,lightgbm]
 
-        # Case 5 - run other models except those are given as aruments for one time
+        # Case 6 - run other models except those are given as aruments for one time
         python run_all_model.py --models=[mlp,tft,sfm] --exclude=True
 
     """
@@ -237,7 +242,7 @@ def run(times=1, models=None, exclude=False):
         env_path, python_path, conda_activate = create_env()
         # get all files
         sys.stderr.write("Retrieving files...\n")
-        yaml_path, req_path = get_all_files(folders[fn])
+        yaml_path, req_path = get_all_files(folders[fn], dataset)
         sys.stderr.write("\n")
         # install requirements.txt
         sys.stderr.write("Installing requirements.txt...\n")
@@ -291,7 +296,8 @@ def run(times=1, models=None, exclude=False):
     pprint(errors)
     sys.stderr.write("\n")
     # move results folder
-    shutil.move(exp_path, exp_path + f"_{datetime.now().strftime('%Y-%m-%d_%H:%M:%S')}")
+    shutil.move(exp_path, exp_path + f"_{dataset}_{datetime.now().strftime('%Y-%m-%d_%H:%M:%S')}")
+    shutil.move("table.md", f"table_{dataset}_{datetime.now().strftime('%Y-%m-%d_%H:%M:%S')}.md")
 
 
 if __name__ == "__main__":
diff --git a/qlib/__init__.py b/qlib/__init__.py
index e84e48ce8..f79b8c4f5 100644
--- a/qlib/__init__.py
+++ b/qlib/__init__.py
@@ -2,7 +2,7 @@
 # Licensed under the MIT License.
 
 
-__version__ = "0.6.0"
+__version__ = "0.6.0.dev"
 
 
 import os
diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index 638ce22f4..000000000
--- a/requirements.txt
+++ /dev/null
@@ -1,25 +0,0 @@
-requests==2.22.0
-six==1.14.0
-lxml==4.5.0
-statsmodels==0.12.0
-pandas==1.1.2
-matplotlib==3.3.2
-scipy==1.3.3
-numpy==1.17.4
-Cython==0.29.21
-fire==0.3.1
-gevent_socketio==0.3.6
-hyperopt==0.2.4
-lightgbm==3.0.0
-loguru==0.5.3
-plotly==4.10.0
-pymongo==3.11.0
-PyYAML==5.3.1
-redis==3.5.3
-redis_lock==0.2.0
-sacred==0.8.1
-scikit_learn==0.23.2
-torch==1.6.0
-tqdm==4.49.0
-yahooquery==2.2.7
-mlflow==1.12.1
\ No newline at end of file
diff --git a/setup.py b/setup.py
index 0cb23f771..cc495824e 100644
--- a/setup.py
+++ b/setup.py
@@ -11,7 +11,7 @@ NAME = "pyqlib"
 DESCRIPTION = "A Quantitative-research Platform"
 REQUIRES_PYTHON = ">=3.5.0"
 
-VERSION = "0.6.0"
+VERSION = "0.6.0.dev"
 
 # Detect Cython
 try:

From 07fb9031c6c7a07235322fbe2ff70a0083038609 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Fri, 4 Dec 2020 10:47:20 +0800
Subject: [PATCH 11/17] Update setup

---
 examples/run_all_model.py | 2 +-
 setup.py                  | 7 ++++++-
 2 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/examples/run_all_model.py b/examples/run_all_model.py
index 9cc1bd2d6..5223634b2 100644
--- a/examples/run_all_model.py
+++ b/examples/run_all_model.py
@@ -191,7 +191,7 @@ def gen_and_save_md_table(metrics):
 
 # function to run the all the models
 @only_allow_defined_args
-def run(times=1, models=None, dataset='Alpha360', exclude=False):
+def run(times=1, models=None, dataset="Alpha360", exclude=False):
     """
     Please be aware that this function can only work under Linux. MacOS and Windows will be supported in the future.
     Any PR to enhance this method is highly welcomed.
diff --git a/setup.py b/setup.py
index cc495824e..66d836444 100644
--- a/setup.py
+++ b/setup.py
@@ -94,7 +94,12 @@ setup(
     long_description=long_description,
     long_description_content_type="text/markdown",
     python_requires=REQUIRES_PYTHON,
-    packages=find_packages(exclude=("tests",)),
+    packages=find_packages(
+        exclude=(
+            "tests",
+            "examples",
+        )
+    ),
     # if your package is a single module, use this instead of 'packages':
     # py_modules=['qlib'],
     entry_points={

From 99adc514a545b9fde8ea145334af6f32dc4e2427 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Fri, 4 Dec 2020 11:51:45 +0800
Subject: [PATCH 12/17] Update CI

---
 .github/workflows/test.yml |  1 +
 examples/run_all_model.py  | 10 +++++-----
 setup.py                   |  7 +------
 3 files changed, 7 insertions(+), 11 deletions(-)

diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 033d31536..9cc4d8cd4 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -27,6 +27,7 @@ jobs:
       run: |
         pip install --upgrade cython
         pip install numpy jupyter jupyter_contrib_nbextensions
+        pip install -U scipy scikit-learn # installing without this line will cause errors on GitHub Actions, while instsalling locally won't
         python setup.py install
 
     - name: Install Lightgbm for MacOS
diff --git a/examples/run_all_model.py b/examples/run_all_model.py
index 5223634b2..34651227c 100644
--- a/examples/run_all_model.py
+++ b/examples/run_all_model.py
@@ -171,9 +171,9 @@ def get_all_results(folders) -> dict:
 
 
 # function to generate and save markdown table
-def gen_and_save_md_table(metrics):
-    table = "| Model Name | Annualized Return | Information Ratio | Max Drawdown | IC | ICIR | Rank IC | Rank ICIR |\n"
-    table += "|---|---|---|---|---|---|---|---|\n"
+def gen_and_save_md_table(metrics, dataset):
+    table = "| Model Name | Dataset | Annualized Return | Information Ratio | Max Drawdown | IC | ICIR | Rank IC | Rank ICIR |\n"
+    table += "|---|---|---|---|---|---|---|---|---|\n"
     for fn in metrics:
         ar = metrics[fn]["annualized_return_with_cost"]
         ir = metrics[fn]["information_ratio_with_cost"]
@@ -182,7 +182,7 @@ def gen_and_save_md_table(metrics):
         icir = metrics[fn]["icir"]
         ric = metrics[fn]["rank_ic"]
         ricir = metrics[fn]["rank_icir"]
-        table += f"| {fn} | {ar[0]:5.4f}±{ar[1]:2.2f} | {ir[0]:5.4f}±{ir[1]:2.2f}| {md[0]:5.4f}±{md[1]:2.2f} | {ic[0]:5.4f}±{ic[1]:2.2f} | {icir[0]:5.4f}±{icir[1]:2.2f}| {ric[0]:5.4f}±{ric[1]:2.2f} | {ricir[0]:5.4f}±{ricir[1]:2.2f} |\n"
+        table += f"| {fn} | {dataset} | {ar[0]:5.4f}±{ar[1]:2.2f} | {ir[0]:5.4f}±{ir[1]:2.2f}| {md[0]:5.4f}±{md[1]:2.2f} | {ic[0]:5.4f}±{ic[1]:2.2f} | {icir[0]:5.4f}±{icir[1]:2.2f}| {ric[0]:5.4f}±{ric[1]:2.2f} | {ricir[0]:5.4f}±{ricir[1]:2.2f} |\n"
     pprint(table)
     with open("table.md", "w") as f:
         f.write(table)
@@ -289,7 +289,7 @@ def run(times=1, models=None, dataset="Alpha360", exclude=False):
     results = cal_mean_std(results)
     # generating md table
     sys.stderr.write(f"Generating markdown table...\n")
-    gen_and_save_md_table(results)
+    gen_and_save_md_table(results, dataset)
     sys.stderr.write("\n")
     # print erros
     sys.stderr.write(f"Here are some of the errors of the models...\n")
diff --git a/setup.py b/setup.py
index 66d836444..cc495824e 100644
--- a/setup.py
+++ b/setup.py
@@ -94,12 +94,7 @@ setup(
     long_description=long_description,
     long_description_content_type="text/markdown",
     python_requires=REQUIRES_PYTHON,
-    packages=find_packages(
-        exclude=(
-            "tests",
-            "examples",
-        )
-    ),
+    packages=find_packages(exclude=("tests",)),
     # if your package is a single module, use this instead of 'packages':
     # py_modules=['qlib'],
     entry_points={

From 86b0b63771ccfefae9658b84ef63cd7ee45932df Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Fri, 4 Dec 2020 12:55:22 +0800
Subject: [PATCH 13/17] Update table generator

---
 examples/run_all_model.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/examples/run_all_model.py b/examples/run_all_model.py
index 34651227c..c8fdebd84 100644
--- a/examples/run_all_model.py
+++ b/examples/run_all_model.py
@@ -137,7 +137,7 @@ def get_all_folders(models, exclude) -> dict:
 # function to get all the files under the model folder
 def get_all_files(folder_path, dataset) -> (str, str):
     yaml_path = str(Path(f"{folder_path}") / f"*{dataset}*.yaml")
-    req_path = str(Path(f"{folder_path}") / f"*{dataset}*.txt")
+    req_path = str(Path(f"{folder_path}") / f"*.txt")
     return glob.glob(yaml_path)[0], glob.glob(req_path)[0]
 
 
@@ -172,17 +172,17 @@ def get_all_results(folders) -> dict:
 
 # function to generate and save markdown table
 def gen_and_save_md_table(metrics, dataset):
-    table = "| Model Name | Dataset | Annualized Return | Information Ratio | Max Drawdown | IC | ICIR | Rank IC | Rank ICIR |\n"
+    table = "| Model Name | Dataset | IC | ICIR | Rank IC | Rank ICIR | Annualized Return | Information Ratio | Max Drawdown |\n"
     table += "|---|---|---|---|---|---|---|---|---|\n"
     for fn in metrics:
-        ar = metrics[fn]["annualized_return_with_cost"]
-        ir = metrics[fn]["information_ratio_with_cost"]
-        md = metrics[fn]["max_drawdown_with_cost"]
         ic = metrics[fn]["ic"]
         icir = metrics[fn]["icir"]
         ric = metrics[fn]["rank_ic"]
         ricir = metrics[fn]["rank_icir"]
-        table += f"| {fn} | {dataset} | {ar[0]:5.4f}±{ar[1]:2.2f} | {ir[0]:5.4f}±{ir[1]:2.2f}| {md[0]:5.4f}±{md[1]:2.2f} | {ic[0]:5.4f}±{ic[1]:2.2f} | {icir[0]:5.4f}±{icir[1]:2.2f}| {ric[0]:5.4f}±{ric[1]:2.2f} | {ricir[0]:5.4f}±{ricir[1]:2.2f} |\n"
+        ar = metrics[fn]["annualized_return_with_cost"]
+        ir = metrics[fn]["information_ratio_with_cost"]
+        md = metrics[fn]["max_drawdown_with_cost"]
+        table += f"| {fn} | {dataset} | {ic[0]:5.4f}±{ic[1]:2.2f} | {icir[0]:5.4f}±{icir[1]:2.2f}| {ric[0]:5.4f}±{ric[1]:2.2f} | {ricir[0]:5.4f}±{ricir[1]:2.2f} | {ar[0]:5.4f}±{ar[1]:2.2f} | {ir[0]:5.4f}±{ir[1]:2.2f}| {md[0]:5.4f}±{md[1]:2.2f} |\n"
     pprint(table)
     with open("table.md", "w") as f:
         f.write(table)

From 2fb7774927ba91032f8ea28f422a4aa0ff2b3899 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Fri, 4 Dec 2020 13:02:09 +0800
Subject: [PATCH 14/17] Update config names

---
 CHANGES.rst                                                   | 2 +-
 ..._config_alstm.yaml => workflow_config_alstm_Alpha360.yaml} | 2 +-
 ...g_catboost.yaml => workflow_config_catboost_Alpha158.yaml} | 0
 ...ow_config_gats.yaml => workflow_config_gats_Alpha360.yaml} | 2 +-
 ...flow_config_gru.yaml => workflow_config_gru_Alpha360.yaml} | 2 +-
 ...ow_config_lstm.yaml => workflow_config_lstm_Alpha360.yaml} | 2 +-
 ...g_lightgbm.yaml => workflow_config_lightgbm_Alpha158.yaml} | 0
 ...onfig_linear.yaml => workflow_config_linear_Alpha158.yaml} | 0
 ...flow_config_mlp.yaml => workflow_config_mlp_Alpha158.yaml} | 0
 ...flow_config_sfm.yaml => workflow_config_sfm_Alpha360.yaml} | 2 +-
 ...flow_config_tft.yaml => workflow_config_tft_Alpha158.yaml} | 0
 ...fig_xgboost.yaml => workflow_config_xgboost_Alpha158.yaml} | 0
 qlib/contrib/data/handler.py                                  | 4 ++--
 13 files changed, 8 insertions(+), 8 deletions(-)
 rename examples/benchmarks/ALSTM/{workflow_config_alstm.yaml => workflow_config_alstm_Alpha360.yaml} (98%)
 rename examples/benchmarks/CatBoost/{workflow_config_catboost.yaml => workflow_config_catboost_Alpha158.yaml} (100%)
 rename examples/benchmarks/GATs/{workflow_config_gats.yaml => workflow_config_gats_Alpha360.yaml} (98%)
 rename examples/benchmarks/GRU/{workflow_config_gru.yaml => workflow_config_gru_Alpha360.yaml} (98%)
 rename examples/benchmarks/LSTM/{workflow_config_lstm.yaml => workflow_config_lstm_Alpha360.yaml} (98%)
 rename examples/benchmarks/LightGBM/{workflow_config_lightgbm.yaml => workflow_config_lightgbm_Alpha158.yaml} (100%)
 rename examples/benchmarks/Linear/{workflow_config_linear.yaml => workflow_config_linear_Alpha158.yaml} (100%)
 rename examples/benchmarks/MLP/{workflow_config_mlp.yaml => workflow_config_mlp_Alpha158.yaml} (100%)
 rename examples/benchmarks/SFM/{workflow_config_sfm.yaml => workflow_config_sfm_Alpha360.yaml} (98%)
 rename examples/benchmarks/TFT/{workflow_config_tft.yaml => workflow_config_tft_Alpha158.yaml} (100%)
 rename examples/benchmarks/XGBoost/{workflow_config_xgboost.yaml => workflow_config_xgboost_Alpha158.yaml} (100%)

diff --git a/CHANGES.rst b/CHANGES.rst
index 1b0982242..114d577f3 100644
--- a/CHANGES.rst
+++ b/CHANGES.rst
@@ -114,7 +114,7 @@ Version 0.4.1
 Version 0.4.2
 --------------------
 - Refactor DataHandler
-- Add ``ALPHA360`` DataHandler
+- Add ``Alpha360`` DataHandler
 
 
 Version 0.4.3
diff --git a/examples/benchmarks/ALSTM/workflow_config_alstm.yaml b/examples/benchmarks/ALSTM/workflow_config_alstm_Alpha360.yaml
similarity index 98%
rename from examples/benchmarks/ALSTM/workflow_config_alstm.yaml
rename to examples/benchmarks/ALSTM/workflow_config_alstm_Alpha360.yaml
index 37dceaacb..6226cdaf2 100644
--- a/examples/benchmarks/ALSTM/workflow_config_alstm.yaml
+++ b/examples/benchmarks/ALSTM/workflow_config_alstm_Alpha360.yaml
@@ -61,7 +61,7 @@ task:
         module_path: qlib.data.dataset
         kwargs:
             handler:
-                class: ALPHA360
+                class: Alpha360
                 module_path: qlib.contrib.data.handler
                 kwargs: *data_handler_config
             segments:
diff --git a/examples/benchmarks/CatBoost/workflow_config_catboost.yaml b/examples/benchmarks/CatBoost/workflow_config_catboost_Alpha158.yaml
similarity index 100%
rename from examples/benchmarks/CatBoost/workflow_config_catboost.yaml
rename to examples/benchmarks/CatBoost/workflow_config_catboost_Alpha158.yaml
diff --git a/examples/benchmarks/GATs/workflow_config_gats.yaml b/examples/benchmarks/GATs/workflow_config_gats_Alpha360.yaml
similarity index 98%
rename from examples/benchmarks/GATs/workflow_config_gats.yaml
rename to examples/benchmarks/GATs/workflow_config_gats_Alpha360.yaml
index 0ab0cae8d..d778c9b1b 100644
--- a/examples/benchmarks/GATs/workflow_config_gats.yaml
+++ b/examples/benchmarks/GATs/workflow_config_gats_Alpha360.yaml
@@ -62,7 +62,7 @@ task:
         module_path: qlib.data.dataset
         kwargs:
             handler:
-                class: ALPHA360
+                class: Alpha360
                 module_path: qlib.contrib.data.handler
                 kwargs: *data_handler_config
             segments:
diff --git a/examples/benchmarks/GRU/workflow_config_gru.yaml b/examples/benchmarks/GRU/workflow_config_gru_Alpha360.yaml
similarity index 98%
rename from examples/benchmarks/GRU/workflow_config_gru.yaml
rename to examples/benchmarks/GRU/workflow_config_gru_Alpha360.yaml
index 64ae3437c..2494d40f0 100644
--- a/examples/benchmarks/GRU/workflow_config_gru.yaml
+++ b/examples/benchmarks/GRU/workflow_config_gru_Alpha360.yaml
@@ -60,7 +60,7 @@ task:
         module_path: qlib.data.dataset
         kwargs:
             handler:
-                class: ALPHA360
+                class: Alpha360
                 module_path: qlib.contrib.data.handler
                 kwargs: *data_handler_config
             segments:
diff --git a/examples/benchmarks/LSTM/workflow_config_lstm.yaml b/examples/benchmarks/LSTM/workflow_config_lstm_Alpha360.yaml
similarity index 98%
rename from examples/benchmarks/LSTM/workflow_config_lstm.yaml
rename to examples/benchmarks/LSTM/workflow_config_lstm_Alpha360.yaml
index b857d97d4..2aa5fd061 100644
--- a/examples/benchmarks/LSTM/workflow_config_lstm.yaml
+++ b/examples/benchmarks/LSTM/workflow_config_lstm_Alpha360.yaml
@@ -60,7 +60,7 @@ task:
         module_path: qlib.data.dataset
         kwargs:
             handler:
-                class: ALPHA360
+                class: Alpha360
                 module_path: qlib.contrib.data.handler
                 kwargs: *data_handler_config
             segments:
diff --git a/examples/benchmarks/LightGBM/workflow_config_lightgbm.yaml b/examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158.yaml
similarity index 100%
rename from examples/benchmarks/LightGBM/workflow_config_lightgbm.yaml
rename to examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158.yaml
diff --git a/examples/benchmarks/Linear/workflow_config_linear.yaml b/examples/benchmarks/Linear/workflow_config_linear_Alpha158.yaml
similarity index 100%
rename from examples/benchmarks/Linear/workflow_config_linear.yaml
rename to examples/benchmarks/Linear/workflow_config_linear_Alpha158.yaml
diff --git a/examples/benchmarks/MLP/workflow_config_mlp.yaml b/examples/benchmarks/MLP/workflow_config_mlp_Alpha158.yaml
similarity index 100%
rename from examples/benchmarks/MLP/workflow_config_mlp.yaml
rename to examples/benchmarks/MLP/workflow_config_mlp_Alpha158.yaml
diff --git a/examples/benchmarks/SFM/workflow_config_sfm.yaml b/examples/benchmarks/SFM/workflow_config_sfm_Alpha360.yaml
similarity index 98%
rename from examples/benchmarks/SFM/workflow_config_sfm.yaml
rename to examples/benchmarks/SFM/workflow_config_sfm_Alpha360.yaml
index 5a0448cfe..a23fe3854 100644
--- a/examples/benchmarks/SFM/workflow_config_sfm.yaml
+++ b/examples/benchmarks/SFM/workflow_config_sfm_Alpha360.yaml
@@ -63,7 +63,7 @@ task:
         module_path: qlib.data.dataset
         kwargs:
             handler:
-                class: ALPHA360
+                class: Alpha360
                 module_path: qlib.contrib.data.handler
                 kwargs: *data_handler_config
             segments:
diff --git a/examples/benchmarks/TFT/workflow_config_tft.yaml b/examples/benchmarks/TFT/workflow_config_tft_Alpha158.yaml
similarity index 100%
rename from examples/benchmarks/TFT/workflow_config_tft.yaml
rename to examples/benchmarks/TFT/workflow_config_tft_Alpha158.yaml
diff --git a/examples/benchmarks/XGBoost/workflow_config_xgboost.yaml b/examples/benchmarks/XGBoost/workflow_config_xgboost_Alpha158.yaml
similarity index 100%
rename from examples/benchmarks/XGBoost/workflow_config_xgboost.yaml
rename to examples/benchmarks/XGBoost/workflow_config_xgboost_Alpha158.yaml
diff --git a/qlib/contrib/data/handler.py b/qlib/contrib/data/handler.py
index 6b3de336d..88a1f0680 100644
--- a/qlib/contrib/data/handler.py
+++ b/qlib/contrib/data/handler.py
@@ -43,7 +43,7 @@ _DEFAULT_INFER_PROCESSORS = [
 ]
 
 
-class ALPHA360(DataHandlerLP):
+class Alpha360(DataHandlerLP):
     def __init__(
         self,
         instruments="csi500",
@@ -119,7 +119,7 @@ class ALPHA360(DataHandlerLP):
         return fields, names
 
 
-class ALPHA360vwap(ALPHA360):
+class Alpha360vwap(Alpha360):
     def get_label_config(self):
         return (["Ref($vwap, -2)/Ref($vwap, -1) - 1"], ["LABEL0"])
 

From 895b1e794428e54618a1316fead63dbfd2324521 Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Fri, 4 Dec 2020 13:10:45 +0800
Subject: [PATCH 15/17] Update CI

---
 .github/workflows/test.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 9cc4d8cd4..261599401 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -57,4 +57,4 @@ jobs:
 
     - name: Test workflow by config
       run: |
-        qrun examples/benchmarks/LightGBM/workflow_config_lightgbm.yaml 
+        qrun examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158.yaml 

From eef90c7901a792392471fdc0faae090033f1fbcb Mon Sep 17 00:00:00 2001
From: Jactus <dw1920@nyu.edu>
Date: Fri, 4 Dec 2020 14:25:26 +0800
Subject: [PATCH 16/17] Update readme

---
 README.md | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 1999160a1..b58456291 100644
--- a/README.md
+++ b/README.md
@@ -27,10 +27,10 @@ For more details, please refer to our paper ["Qlib: An AI-oriented Quantitative
   - [Data Preparation](#data-preparation)
   - [Auto Quant Research Workflow](#auto-quant-research-workflow)
   - [Building Customized Quant Research Workflow by Code](#building-customized-quant-research-workflow-by-code)
-- [Quant Model Zoo](#quant-model-zoo)
+- [**Quant Model Zoo**](#quant-model-zoo)
   - [Run a single model](#run-a-single-model)
   - [Run multiple models](#run-multiple-models)
-- [Quant Dataset Zoo](#quant-dataset-zoo)
+- [**Quant Dataset Zoo**](#quant-dataset-zoo)
 - [More About Qlib](#more-about-qlib)
 - [Offline Mode and Online Mode](#offline-mode-and-online-mode)
   - [Performance of Qlib Data Server](#performance-of-qlib-data-server)
@@ -153,6 +153,7 @@ Qlib provides a tool named `qrun` to run the whole workflow automatically (inclu
     annualized_return  0.128982
     information_ratio  1.444287
     max_drawdown      -0.091078
+    ```
 
 
 
@@ -234,7 +235,7 @@ Dataset plays a very important role in Quant. Here is a list of the datasets bui
 | Dataset                                    | US Market | China Market |
 | --                                         | --        | --           |
 | [Alpha360](./qlib/contrib/data/handler.py) |  √        |  √           |
-| [Alpha158](./qlib/contrib/data/handler.py) |  √        |  √           | 
+| [Alpha158](./qlib/contrib/data/handler.py) |  √        |  √           |
 
 [Here](https://qlib.readthedocs.io/en/latest/advanced/alpha.html) is a tutorial to build dataset with `Qlib`.
 Your PR to build new Quant dataset is highly welcomed.

From 46396c229a128e616ba1add4a1eacff24e7c217a Mon Sep 17 00:00:00 2001
From: Dingsu Wang <dingsu.wang@gmail.com>
Date: Fri, 4 Dec 2020 14:28:13 +0800
Subject: [PATCH 17/17] Update README.md

---
 README.md | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/README.md b/README.md
index b58456291..de7dd1cf0 100644
--- a/README.md
+++ b/README.md
@@ -153,10 +153,6 @@ Qlib provides a tool named `qrun` to run the whole workflow automatically (inclu
     annualized_return  0.128982
     information_ratio  1.444287
     max_drawdown      -0.091078
-    ```
-
-
-
     ```
     Here are detailed documents for `qrun` and [workflow](https://qlib.readthedocs.io/en/latest/component/workflow.html).