From 2acacb00a8b9f2c93ed82a0d16614e85cdc5a877 Mon Sep 17 00:00:00 2001
From: lucas_miranda <lucasmiranda42@gmail.com>
Date: Wed, 10 Mar 2021 13:24:36 +0100
Subject: [PATCH] Added nose2body to rule_based_annotation()
---
deepof/models.py | 10 +--
deepof_experiments.smk | 145 +++++++++++++++++++++--------------------
2 files changed, 78 insertions(+), 77 deletions(-)
diff --git a/deepof/models.py b/deepof/models.py
index b056a744..338e259d 100644
--- a/deepof/models.py
+++ b/deepof/models.py
@@ -559,8 +559,8 @@ class SEQ_2_SEQ_GMVAE:
encoder = Model_E3(encoder)
encoder = BatchNormalization()(encoder)
encoder = Dropout(self.DROPOUT_RATE)(encoder)
- encoder = Sequential(Model_E4)(encoder)
- encoder = BatchNormalization()(encoder)
+ # encoder = Sequential(Model_E4)(encoder)
+ # encoder = BatchNormalization()(encoder)
# encoding_shuffle = deepof.model_utils.MCDropout(self.DROPOUT_RATE)(encoder)
z_cat = Dense(
@@ -670,9 +670,9 @@ class SEQ_2_SEQ_GMVAE:
# Define and instantiate generator
g = Input(shape=self.ENCODING)
- generator = Sequential(Model_D1)(g)
- generator = Model_B1(generator)
- generator = Model_D2(generator)
+ # generator = Sequential(Model_D1)(g)
+ # generator = Model_B1(generator)
+ generator = Model_D2(g)
generator = Model_B2(generator)
generator = Model_D3(generator)
generator = Model_D4(generator)
diff --git a/deepof_experiments.smk b/deepof_experiments.smk
index 6d21a0b7..7e7fa781 100644
--- a/deepof_experiments.smk
+++ b/deepof_experiments.smk
@@ -23,22 +23,23 @@ 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(
+ # os.path.join(
+ # outpath,
+ # "coarse_hyperparameter_tuning/trained_weights/GMVAE_loss={loss}_k={k}_encoding={enc}_final_weights.h5",
+ # ),
+ # loss=losses,
+ # k=cluster_numbers,
+ # enc=encodings,
+ # ),
expand(
- os.path.join(
- outpath,
- "coarse_hyperparameter_tuning/trained_weights/GMVAE_loss={loss}_k={k}_encoding={enc}_final_weights.h5",
- ),
- loss=losses,
- k=cluster_numbers,
- enc=encodings,
- ), # expand(
- # "/psycl/g/mpsstatgen/lucas/DLC/DLC_autoencoders/DeepOF/deepof/logs/latent_regularization_experiments/trained_weights/"
- # "GMVAE_loss={loss}_encoding={encs}_k={k}_latreg={latreg}_final_weights.h5",
- # loss=losses,
- # encs=encodings,
- # k=cluster_numbers,
- # latreg=latent_reg,
- # )
+ "/psycl/g/mpsstatgen/lucas/DLC/DLC_autoencoders/DeepOF/deepof/logs/latent_regularization_experiments/trained_weights/"
+ "GMVAE_loss={loss}_encoding={encs}_k={k}_latreg={latreg}_final_weights.h5",
+ loss=losses,
+ encs=encodings,
+ k=cluster_numbers,
+ latreg=latent_reg,
+ )
# expand(
# "/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",
@@ -78,60 +79,60 @@ rule coarse_hyperparameter_tuning:
"--hpt-trials 1"
-# rule latent_regularization_experiments:
-# input:
-# data_path=ancient("/psycl/g/mpsstatgen/lucas/DLC/DLC_models/deepof_single_topview/"),
-# output:
-# trained_models=os.path.join(
-# outpath,
-# "latent_regularization_experiments/trained_weights/GMVAE_loss={loss}_encoding={encs}_k={k}_latreg={latreg}_final_weights.h5",
-# ),
-# shell:
-# "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 "
-# "--latent-reg {wildcards.latreg} "
-# "--loss {wildcards.loss} "
-# "--kl-warmup 20 "
-# "--mmd-warmup 20 "
-# "--montecarlo-kl 10 "
-# "--encoding-size {wildcards.encs} "
-# "--batch-size 256 "
-# "--window-size 24 "
-# "--window-step 12 "
-# "--exclude-bodyparts Tail_base,Tail_1,Tail_2,Tail_tip "
-# "--output-path {outpath}latent_regularization_experiments"
-#
-#
-# rule explore_phenotype_classification:
-# input:
-# data_path="/psycl/g/mpsstatgen/lucas/DLC/DLC_models/deepof_single_topview/",
-# output:
-# trained_models=os.path.join(
-# outpath,
-# "pheno_classification_experiments/trained_weights/GMVAE_loss={loss}_encoding={encs}_k={k}_pheno={phenos}_run_1_final_weights.h5",
-# ),
-# shell:
-# "pipenv run python -m deepof.train_model "
-# "--train-path {input.data_path} "
-# "--val-num 15 "
-# "--components {wildcards.k} "
-# "--input-type coords "
-# "--predictor 0 "
-# "--phenotype-classifier {wildcards.phenos} "
-# "--variational True "
-# "--loss {wildcards.loss} "
-# "--kl-warmup 20 "
-# "--mmd-warmup 20 "
-# "--montecarlo-kl 10 "
-# "--encoding-size {wildcards.encs} "
-# "--batch-size 256 "
-# "--window-size 11 "
-# "--window-step 11 "
-# "--stability-check 3 "
-# "--output-path {outpath}pheno_classification_experiments"
+rule latent_regularization_experiments:
+ input:
+ data_path=ancient("/psycl/g/mpsstatgen/lucas/DLC/DLC_models/deepof_single_topview/"),
+ output:
+ trained_models=os.path.join(
+ outpath,
+ "latent_regularization_experiments/trained_weights/GMVAE_loss={loss}_encoding={encs}_k={k}_latreg={latreg}_final_weights.h5",
+ ),
+ shell:
+ "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 "
+ "--latent-reg {wildcards.latreg} "
+ "--loss {wildcards.loss} "
+ "--kl-warmup 20 "
+ "--mmd-warmup 20 "
+ "--montecarlo-kl 10 "
+ "--encoding-size {wildcards.encs} "
+ "--batch-size 256 "
+ "--window-size 24 "
+ "--window-step 12 "
+ "--exclude-bodyparts Tail_base,Tail_1,Tail_2,Tail_tip "
+ "--output-path {outpath}latent_regularization_experiments"
+
+
+rule explore_phenotype_classification:
+ input:
+ data_path="/psycl/g/mpsstatgen/lucas/DLC/DLC_models/deepof_single_topview/",
+ output:
+ trained_models=os.path.join(
+ outpath,
+ "pheno_classification_experiments/trained_weights/GMVAE_loss={loss}_encoding={encs}_k={k}_pheno={phenos}_run_1_final_weights.h5",
+ ),
+ shell:
+ "pipenv run python -m deepof.train_model "
+ "--train-path {input.data_path} "
+ "--val-num 15 "
+ "--components {wildcards.k} "
+ "--input-type coords "
+ "--predictor 0 "
+ "--phenotype-classifier {wildcards.phenos} "
+ "--variational True "
+ "--loss {wildcards.loss} "
+ "--kl-warmup 20 "
+ "--mmd-warmup 20 "
+ "--montecarlo-kl 10 "
+ "--encoding-size {wildcards.encs} "
+ "--batch-size 256 "
+ "--window-size 11 "
+ "--window-step 11 "
+ "--stability-check 3 "
+ "--output-path {outpath}pheno_classification_experiments"
--
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