Refactored train_utils.py

deepof_experiments.smk

@@ -13,7 +13,7 @@ Plot rule graph: snakemake --snakefile deepof_experiments.smk --forceall --ruleg
 
 import os
 
-outpath = "/u/lucasmir/DLC/DLC_autoencoders/DeepOF/deepof/logs/"
+outpath = "/psycl/g/mpsstatgen/lucas/DLC/DLC_autoencoders/DeepOF/deepof/logs/"
 losses = ["ELBO"]  # , "MMD", "ELBO+MMD"]
 encodings = [4, 6, 8]  # [2, 4, 6, 8, 10, 12, 14, 16]
 cluster_numbers = [10, 15, 20]  # [1, 5, 10, 15, 20]
@@ -22,20 +22,20 @@ pheno_weights = [0.01, 0.1, 0.25, 0.5, 1.0, 2.0, 4.0, 10.0, 100.0]
 
 rule deepof_experiments:
     input:
-        expand( "/u/lucasmir/DLC/DLC_autoencoders/DeepOF/deepof/logs/hyperparameter_tuning/trained_weights/"
-                "GMVAE_loss={loss}_encoding=2_k=15_run_1_final_weights.h5",
+        expand( "/psycl/g/mpsstatgen/lucas/DLC/DLC_autoencoders/DeepOF/deepof/logs/hyperparameter_tuning/trained_weights/"
+                "GMVAE_loss={loss}_encoding=2_run_1_final_weights.h5",
                 loss=losses,
         )
 
         # expand(
-        #     "/u/lucasmir/DLC/DLC_autoencoders/DeepOF/deepof/logs/dimension_and_loss_experiments/trained_weights/"
+        #     "/psycl/g/mpsstatgen/lucas/DLC/DLC_autoencoders/DeepOF/deepof/logs/dimension_and_loss_experiments/trained_weights/"
         #     "GMVAE_loss={loss}_encoding={encs}_k={k}_run_1_final_weights.h5",
         #     loss=losses,
         #     encs=encodings,
         #     k=cluster_numbers,
         # ),
         # expand(
-        #     "/u/lucasmir/DLC/DLC_autoencoders/DeepOF/deepof/logs/pheno_classification_experiments/trained_weights/"
+        #     "/psycl/g/mpsstatgen/lucas/DLC/DLC_autoencoders/DeepOF/deepof/logs/pheno_classification_experiments/trained_weights/"
         #     "GMVAE_loss={loss}_encoding={encs}_k={k}_pheno={phenos}_run_1_final_weights.h5",
         #     loss=losses,
         #     encs=encodings,
@@ -46,7 +46,7 @@ rule deepof_experiments:
 
 rule coarse_hyperparameter_tuning:
     input:
-        data_path="/u/lucasmir/DLC/DLC_models/deepof_single_topview/",
+        data_path="/psycl/g/mpsstatgen/lucas/DLC/DLC_models/deepof_single_topview/",
     output:
         trained_models=os.path.join(
             outpath,
@@ -75,7 +75,7 @@ rule coarse_hyperparameter_tuning:
 
 # rule explore_encoding_dimension_and_loss_function:
 #     input:
-#         data_path=ancient("/u/lucasmir/DLC/DLC_models/deepof_single_topview/"),
+#         data_path=ancient("/psycl/g/mpsstatgen/lucas/DLC/DLC_models/deepof_single_topview/"),
 #     output:
 #         trained_models=os.path.join(
 #             outpath,
@@ -105,7 +105,7 @@ rule coarse_hyperparameter_tuning:
 #
 # rule explore_phenotype_classification:
 #     input:
-#         data_path="/u/lucasmir/DLC/DLC_models/deepof_single_topview/",
+#         data_path="/psycl/g/mpsstatgen/lucas/DLC/DLC_models/deepof_single_topview/",
 #     output:
 #         trained_models=os.path.join(
 #             outpath,
@@ -130,8 +130,3 @@ rule coarse_hyperparameter_tuning:
 #         "--window-step 11 "
 #         "--stability-check 3  "
 #         "--output-path {outpath}pheno_classification_experiments"
-
-
-
-
-"pipenv run python -m deepof.train_model --train-path {input.data_path} --val-num 5 --components {wildcards.k} --input-type coords --predictor 0 --phenotype-classifier 0 --variational True --loss {wildcards.loss} --kl-warmup 20 --mmd-warmup 20 --montecarlo-kl 10 --encoding-size {wildcards.encs} --batch-size 256 --window-size 24 --window-step 6 --exclude-bodyparts Tail_base,Tail_1,Tail_2,Tail_tip --stability-check 3 --output-path {outpath}dimension_and_loss_experiments"
\ No newline at end of file