From a1bf6efd5283fde7e508978a1d152e61e6c2c08c Mon Sep 17 00:00:00 2001 From: Aaron Cutright Date: Mon, 15 Mar 2021 23:39:11 -0400 Subject: [PATCH] Add documentation for previous commits --- gamestonk_terminal/prediction_techniques/README.md | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/gamestonk_terminal/prediction_techniques/README.md b/gamestonk_terminal/prediction_techniques/README.md index 2104aeadffe..bb0a829d05e 100644 --- a/gamestonk_terminal/prediction_techniques/README.md +++ b/gamestonk_terminal/prediction_techniques/README.md @@ -164,6 +164,10 @@ MulitLayer Perceptron: * -o : optimization technique. Default adam. * -l : loss function. Default mae. * -e : end date (format YYYY-MM-DD) of the stock - Backtesting. Default None. + * --xla_cpu: if present, will enable XLA for CPU (overrides environment variables during run). + * --xla_gpu: if present, will enable XLA for GPU (overrides environment variables during run). + * --force_allow_gpu_growth: if true, will force TensorFlow to allow GPU memory usage to grow as needed. Otherwise will allocate 100% of available GPU memory when CUDA is set up. Default true. + * --batch_size: batch size for model training, should not be used unless advanced user. Default None. Due to the complexity of defining a model through command line, one can define it in: [config_neural_network_models.txt](/config_neural_network_models.py) ``` @@ -196,6 +200,10 @@ Recurrent Neural Network: * -o : optimization technique. Default adam. * -l : loss function. Default mae. * -e : end date (format YYYY-MM-DD) of the stock - Backtesting. Default None. + * --xla_cpu: if present, will enable XLA for CPU (overrides environment variables during run). + * --xla_gpu: if present, will enable XLA for GPU (overrides environment variables during run). + * --force_allow_gpu_growth: if true, will force TensorFlow to allow GPU memory usage to grow as needed. Otherwise will allocate 100% of available GPU memory when CUDA is set up. Default true. + * --batch_size: batch size for model training, should not be used unless advanced user. Default None. Due to the complexity of defining a model through command line, one can define it in: [config_neural_network_models.txt](/config_neural_network_models.py) ``` @@ -228,8 +236,12 @@ Long-Short Term Memory: * -o : optimization technique. Default adam. * -l : loss function. Default mae. * -e : end date (format YYYY-MM-DD) of the stock - Backtesting. Default None. + * --xla_cpu: if present, will enable XLA for CPU (overrides environment variables during run). + * --xla_gpu: if present, will enable XLA for GPU (overrides environment variables during run). + * --force_allow_gpu_growth: if true, will force TensorFlow to allow GPU memory usage to grow as needed. Otherwise will allocate 100% of available GPU memory when CUDA is set up. Default true. + * --batch_size: batch size for model training, should not be used unless advanced user. Default None. -Due to the complexity of defining a model through command line, one can define it in: [config_neural_network_models.txt](/config_neural_network_models.py) +Due to the complexity of defining a model through command line, one can define it in: [config_neural_network_models.py](/config_neural_network_models.py) ``` Long_Short_Term_Memory \ = [ {'LSTM':