diff --git a/2a_model.R b/2a_model.R index fa2e0d74..50829fee 100644 --- a/2a_model.R +++ b/2a_model.R @@ -189,14 +189,14 @@ p2a_targets_list <- list( list(model_id = "0_baseline_LSTM", snakefile_dir = "0_baseline_LSTM", config_path = stringr::str_remove(p2a_config_baseline_LSTM_yml, "2a_model/src/models/")), - # the 1_ models use the same model and therefore the same Snakefile - # as the 0_baseline_LSTM run - list(model_id = "1_metab_multitask", - snakefile_dir = "0_baseline_LSTM", - config_path = stringr::str_remove(p2a_config_metab_multitask_yml, "2a_model/src/models/")), - list(model_id = "1a_multitask_do_gpp_er", - snakefile_dir = "0_baseline_LSTM", - config_path = stringr::str_remove(p2a_config_1a_metab_multitask_yml, "2a_model/src/models/")), + #the 1_ models use the same model and therefore the same Snakefile + #as the 0_baseline_LSTM run + #list(model_id = "1_metab_multitask", + #snakefile_dir = "0_baseline_LSTM", + #config_path = stringr::str_remove(p2a_config_metab_multitask_yml, "2a_model/src/models/")), + #list(model_id = "1a_multitask_do_gpp_er", + #snakefile_dir = "0_baseline_LSTM", + #config_path = stringr::str_remove(p2a_config_1a_metab_multitask_yml, "2a_model/src/models/")), list(model_id = "2_multitask_dense", snakefile_dir = "2_multitask_dense", config_path = stringr::str_remove(p2a_config_multitask_dense_yml, "2a_model/src/models/")) @@ -219,16 +219,18 @@ p2a_targets_list <- list( # this path is relative to the Snakefile prepped_data_file <- file.path("../../../out/models",p2a_model_ids$model_id, "prepped.npz") + # make sure the directory is unlocked (this has been a hangup for me) + system(stringr::str_glue("snakemake -s {snakefile_path} --configfile {config_path} --unlock")) # First create the prepped data files if they are not already. # These are needed to make the predictions. system(stringr::str_glue("snakemake {prepped_data_file} -s {snakefile_path} --configfile {config_path} -j")) # Then touch all of the existing files. This makes the weights "up-to-date" # so snakemake doesn't train the models again - system(stringr::str_glue("snakemake -s {snakefile_path} --configfile {config_path} -j --touch")) + system(stringr::str_glue("snakemake -s {snakefile_path} --configfile {config_path} -j --touch --rerun-incomplete")) # then run the snakemake pipeline to produce the predictions and metric files - system(stringr::str_glue("snakemake -s {snakefile_path} --configfile {config_path} -j --rerun-incomplete")) + system(stringr::str_glue("snakemake -s {snakefile_path} --configfile {config_path} -j --rerun-incomplete ")) # print out the metrics file name for the target file.path("2a_model/out/models", p2a_model_ids$model_id, "exp_overall_metrics.csv") diff --git a/2a_model/out/models/0_baseline_LSTM/nstates_10/nep_100/rep_0/train_weights/.data-00000-of-00001 b/2a_model/out/models/0_baseline_LSTM/nstates_10/nep_100/rep_0/train_weights/.data-00000-of-00001 index b77125d2..fcad4689 100644 Binary files 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b/2a_model/out/models/2_multitask_dense/nstates_10/nep_100/rep_9/train_weights/checkpoint @@ -0,0 +1,2 @@ +model_checkpoint_path: "." +all_model_checkpoint_paths: "." diff --git a/2a_model/out/models/add_weights.sh b/2a_model/out/models/add_weights.sh index 19e8c64b..8cba6777 100644 --- a/2a_model/out/models/add_weights.sh +++ b/2a_model/out/models/add_weights.sh @@ -1,6 +1,6 @@ files=(checkpoint .data-00000-of-00001 .index .snakemake_timestamp) -models=(0_baseline_LSTM 1_metab_multitask 1a_multitask_do_gpp_er) +models=(0_baseline_LSTM 2_multitask_dense) for f in ${files[@]}; do for d in ${models[@]}; do diff --git a/2a_model/src/models/0_baseline_LSTM/config.yml b/2a_model/src/models/0_baseline_LSTM/config.yml index 71f1ec18..6437287f 100644 --- a/2a_model/src/models/0_baseline_LSTM/config.yml +++ b/2a_model/src/models/0_baseline_LSTM/config.yml @@ -1,8 +1,8 @@ -exp_name: "0_baseline_LSTM" +exp_name: 0_baseline_LSTM y_vars: - - "do_min" - - "do_mean" - - "do_max" + - do_min + - do_mean + - do_max lambdas: - 1 - 1 diff --git a/2a_model/src/models/1_metab_multitask/1a_multitask_do_gpp_er.yml b/2a_model/src/models/1_metab_multitask/1a_multitask_do_gpp_er.yml index 9ed098c3..5b5a4c40 100644 --- a/2a_model/src/models/1_metab_multitask/1a_multitask_do_gpp_er.yml +++ b/2a_model/src/models/1_metab_multitask/1a_multitask_do_gpp_er.yml @@ -1,13 +1,13 @@ -exp_name: "1a_multitask_do_gpp_er" +exp_name: 1a_multitask_do_gpp_er y_vars: - - "do_min" - - "do_mean" - - "do_max" - - "GPP" - - "ER" - - "K600" - - "depth" - - "temp.water" + - do_min + - do_mean + - do_max + - GPP + - ER + - K600 + - depth + - temp.water lambdas: - 1 - 1 diff --git a/2a_model/src/models/1_metab_multitask/config.yml b/2a_model/src/models/1_metab_multitask/config.yml index b9be0066..f5487a7b 100644 --- a/2a_model/src/models/1_metab_multitask/config.yml +++ b/2a_model/src/models/1_metab_multitask/config.yml @@ -1,13 +1,13 @@ -exp_name: "1_metab_multitask" +exp_name: 1_metab_multitask y_vars: - - "do_min" - - "do_mean" - - "do_max" - - "GPP" - - "ER" - - "K600" - - "depth" - - "temp.water" + - do_min + - do_mean + - do_max + - GPP + - ER + - K600 + - depth + - temp.water lambdas: - 1 - 1 diff --git a/2a_model/src/models/2_multitask_dense/config.yml b/2a_model/src/models/2_multitask_dense/config.yml index 678c4a5c..75d0bc7a 100644 --- a/2a_model/src/models/2_multitask_dense/config.yml +++ b/2a_model/src/models/2_multitask_dense/config.yml @@ -1,13 +1,13 @@ -exp_name: "2_multitask_dense" +exp_name: 2_multitask_dense y_vars: - - "do_min" - - "do_mean" - - "do_max" - - "GPP" - - "ER" - - "K600" - - "depth" - - "temp.water" + - do_min + - do_mean + - do_max + - GPP + - ER + - K600 + - depth + - temp.water lambdas: - 1 - 1 diff --git a/2a_model/src/models/config_base.yml b/2a_model/src/models/config_base.yml index 0132578a..121068b4 100644 --- a/2a_model/src/models/config_base.yml +++ b/2a_model/src/models/config_base.yml @@ -1,6 +1,6 @@ -out_dir: "../../../out/models" +out_dir: ../../../out/models seed: False -num_replicates: 1 +num_replicates: 10 trn_offset: 1.0 tst_val_offset: 1.0 epochs: 100 @@ -10,12 +10,12 @@ recurrent_dropout: 0.2 finetune_learning_rate: 0.01 early_stopping: False validation_sites: - - "01472104" - - "01473500" - - "01481500" + - '01472104' + - '01473500' + - 01481500 test_sites: - - "01475530" - - "01475548" + - '01475530' + - 01475548 train_start_date: '1980-01-01' train_end_date: '2014-10-01' val_start_date: '2014-10-01' @@ -23,14 +23,34 @@ val_end_date: '2015-10-01' test_start_date: '2015-10-01' test_end_date: '2022-10-01' x_vars: - - "pr" - - "SLOPE" - - "tmmx" - - "tmmn" - - "srad" - - "CAT_BASIN_SLOPE" - - "CAT_ELEV_MEAN" - - "CAT_IMPV11" - - "CAT_CNPY11_BUFF100" - - "CAT_TWI" + - tmmn + - tmmx + - pr + - srad + - SLOPE + - TOTDASQKM + - CAT_BASIN_SLOPE + - TOT_BASIN_SLOPE + - CAT_ELEV_MEAN + - CAT_RDX + - CAT_BFI + - CAT_EWT + - CAT_TWI + - CAT_PPT7100_ANN + - TOT_PPT7100_ANN + - CAT_RUN7100 + - CAT_CNPY11_BUFF100 + - CAT_IMPV11 + - TOT_IMPV11 + - CAT_NLCD11_wetland + - TOT_NLCD11_wetland + - CAT_SANDAVE + - CAT_PERMAVE + - TOT_PERMAVE + - CAT_RFACT + - CAT_WTDEP + - TOT_WTDEP + - CAT_NPDES_MAJ + - CAT_NDAMS2010 + - CAT_NORM_STORAGE2010 diff --git a/_targets.R b/_targets.R index 1c9723b9..e0988beb 100644 --- a/_targets.R +++ b/_targets.R @@ -110,7 +110,7 @@ base_config_options <- list( out_dir = "../../../out/models", # random seed for training; If FALSE, no seed. Otherwise, specify the seed: seed = FALSE, - num_replicates = 1, + num_replicates = 10, trn_offset = 1, tst_val_offset = 1, epochs = 100,