From 9e22e5168b07728298b666672f3dbf0bc20be258 Mon Sep 17 00:00:00 2001 From: Maksim Zayakin Date: Fri, 28 Apr 2023 14:48:40 +0500 Subject: [PATCH] Remove unused `DNNModelPytorch` params (#1470) * Remove lr_decay and lr_decay_steps params More flexible way to pass a scheduler (via callable function) is already supported * remove lr_decay and lr_decay_steps from mlp workflow configs --- .../benchmarks/MLP/workflow_config_mlp_Alpha158.yaml | 2 -- .../MLP/workflow_config_mlp_Alpha158_csi500.yaml | 2 -- .../benchmarks/MLP/workflow_config_mlp_Alpha360.yaml | 2 -- .../MLP/workflow_config_mlp_Alpha360_csi500.yaml | 2 -- qlib/contrib/model/pytorch_nn.py | 10 ---------- 5 files changed, 18 deletions(-) diff --git a/examples/benchmarks/MLP/workflow_config_mlp_Alpha158.yaml b/examples/benchmarks/MLP/workflow_config_mlp_Alpha158.yaml index bc9c3c8ab..b2012ba8c 100644 --- a/examples/benchmarks/MLP/workflow_config_mlp_Alpha158.yaml +++ b/examples/benchmarks/MLP/workflow_config_mlp_Alpha158.yaml @@ -64,8 +64,6 @@ task: kwargs: loss: mse lr: 0.002 - lr_decay: 0.96 - lr_decay_steps: 100 optimizer: adam max_steps: 8000 batch_size: 8192 diff --git a/examples/benchmarks/MLP/workflow_config_mlp_Alpha158_csi500.yaml b/examples/benchmarks/MLP/workflow_config_mlp_Alpha158_csi500.yaml index 3538afd8f..8628898d3 100644 --- a/examples/benchmarks/MLP/workflow_config_mlp_Alpha158_csi500.yaml +++ b/examples/benchmarks/MLP/workflow_config_mlp_Alpha158_csi500.yaml @@ -64,8 +64,6 @@ task: kwargs: loss: mse lr: 0.002 - lr_decay: 0.96 - lr_decay_steps: 100 optimizer: adam max_steps: 8000 batch_size: 8192 diff --git a/examples/benchmarks/MLP/workflow_config_mlp_Alpha360.yaml b/examples/benchmarks/MLP/workflow_config_mlp_Alpha360.yaml index c09fd6e50..359e79202 100644 --- a/examples/benchmarks/MLP/workflow_config_mlp_Alpha360.yaml +++ b/examples/benchmarks/MLP/workflow_config_mlp_Alpha360.yaml @@ -52,8 +52,6 @@ task: kwargs: loss: mse lr: 0.002 - lr_decay: 0.96 - lr_decay_steps: 100 optimizer: adam max_steps: 8000 batch_size: 4096 diff --git a/examples/benchmarks/MLP/workflow_config_mlp_Alpha360_csi500.yaml b/examples/benchmarks/MLP/workflow_config_mlp_Alpha360_csi500.yaml index 7a87e70bb..3862295f6 100644 --- a/examples/benchmarks/MLP/workflow_config_mlp_Alpha360_csi500.yaml +++ b/examples/benchmarks/MLP/workflow_config_mlp_Alpha360_csi500.yaml @@ -52,8 +52,6 @@ task: kwargs: loss: mse lr: 0.002 - lr_decay: 0.96 - lr_decay_steps: 100 optimizer: adam max_steps: 8000 batch_size: 4096 diff --git a/qlib/contrib/model/pytorch_nn.py b/qlib/contrib/model/pytorch_nn.py index ed3d32352..7768b0292 100644 --- a/qlib/contrib/model/pytorch_nn.py +++ b/qlib/contrib/model/pytorch_nn.py @@ -47,10 +47,6 @@ class DNNModelPytorch(Model): layer sizes lr : float learning rate - lr_decay : float - learning rate decay - lr_decay_steps : int - learning rate decay steps optimizer : str optimizer name GPU : int @@ -64,8 +60,6 @@ class DNNModelPytorch(Model): batch_size=2000, early_stop_rounds=50, eval_steps=20, - lr_decay=0.96, - lr_decay_steps=100, optimizer="gd", loss="mse", GPU=0, @@ -93,8 +87,6 @@ class DNNModelPytorch(Model): self.batch_size = batch_size self.early_stop_rounds = early_stop_rounds self.eval_steps = eval_steps - self.lr_decay = lr_decay - self.lr_decay_steps = lr_decay_steps self.optimizer = optimizer.lower() self.loss_type = loss if isinstance(GPU, str): @@ -116,8 +108,6 @@ class DNNModelPytorch(Model): f"\nbatch_size : {batch_size}" f"\nearly_stop_rounds : {early_stop_rounds}" f"\neval_steps : {eval_steps}" - f"\nlr_decay : {lr_decay}" - f"\nlr_decay_steps : {lr_decay_steps}" f"\noptimizer : {optimizer}" f"\nloss_type : {loss}" f"\nseed : {seed}"