docs update

docs/build/html/_modules/domid/algos/builder_ae.html

@@ -309,18 +309,15 @@
           <article class="md-content__inner md-typeset" role="main">
 
   <h1 id="modules-domid-algos-builder-ae--page-root">Source code for domid.algos.builder_ae</h1><div class="highlight"><pre>
-<span></span>import datetime
-
-from domainlab.algos.a_algo_builder import NodeAlgoBuilder
-from domainlab.algos.msels.c_msel import MSelTrLoss
+<span></span>from domainlab.algos.a_algo_builder import NodeAlgoBuilder
 from domainlab.algos.msels.c_msel_oracle import MSelOracleVisitor
+from domainlab.algos.msels.c_msel_val import MSelValPerf
 from domainlab.algos.observers.c_obvisitor_cleanup import ObVisitorCleanUp
 from domainlab.utils.utils_cuda import get_device
-from tensorboardX import SummaryWriter
 
 from domid.algos.observers.b_obvisitor_clustering_only import ObVisitorClusteringOnly
-from domid.models.model_ae import ModelAE
-from domid.trainers.trainer_ae import TrainerCluster
+from domid.models.model_ae import mk_ae
+from domid.trainers.zoo_trainer import TrainerChainNodeGetter
 
 
 <div class="viewcode-block" id="NodeAlgoBuilderAE"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_ae.NodeAlgoBuilderAE">[docs]</a>class NodeAlgoBuilderAE(NodeAlgoBuilder):
@@ -330,31 +327,35 @@ <h1 id="modules-domid-algos-builder-ae--page-root">Source code for domid.algos.b
         """
         task = exp.task
         args = exp.args
-
         device = get_device(args)
 
         zd_dim = args.zd_dim
         d_dim = args.d_dim
         L = args.L
 
-        pretrain = args.pre_tr &gt; 0
-
-        now = "zd_dim_" + str(zd_dim) + "_lr_" + str(args.lr) + "_" + str(datetime.datetime.now())
-        model = ModelAE(
+        model = mk_ae()(
             zd_dim=zd_dim,
             d_dim=d_dim,
             device=device,
-            L=L,
             i_c=task.isize.c,
             i_h=task.isize.h,
             i_w=task.isize.w,
-            args=args,
+            bs=args.bs,
+            prior=args.prior,
+            random_batching=args.random_batching,
+            model_method=args.model_method,
+            pre_tr_weight_path=args.pre_tr_weight_path,
+            feat_extract=args.feat_extract,
         )
-        observer = ObVisitorCleanUp(ObVisitorClusteringOnly(exp, MSelOracleVisitor(MSelTrLoss(max_es=args.es)), device))
-        writer = SummaryWriter(logdir="debug/" + now)
-        trainer = TrainerCluster(model, task, observer, device, writer, pretrain=pretrain, aconf=args)
 
-        return trainer</div></div>
+        observer = ObVisitorCleanUp(
+            ObVisitorClusteringOnly(exp, MSelOracleVisitor(MSelValPerf(max_es=args.es)), device)
+        )
+
+        trainer = TrainerChainNodeGetter(args.trainer)()
+        trainer.init_business(model, task, observer, device, args)
+
+        return trainer, model, observer, device</div></div>
 
 
 <div class="viewcode-block" id="get_node_na"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_ae.get_node_na">[docs]</a>def get_node_na():

docs/build/html/_modules/domid/algos/builder_dec.html

@@ -309,18 +309,15 @@
           <article class="md-content__inner md-typeset" role="main">
 
   <h1 id="modules-domid-algos-builder-dec--page-root">Source code for domid.algos.builder_dec</h1><div class="highlight"><pre>
-<span></span>import datetime
-
-from domainlab.algos.a_algo_builder import NodeAlgoBuilder
-from domainlab.algos.msels.c_msel import MSelTrLoss
+<span></span>from domainlab.algos.a_algo_builder import NodeAlgoBuilder
 from domainlab.algos.msels.c_msel_oracle import MSelOracleVisitor
+from domainlab.algos.msels.c_msel_val import MSelValPerf
 from domainlab.algos.observers.c_obvisitor_cleanup import ObVisitorCleanUp
 from domainlab.utils.utils_cuda import get_device
-from tensorboardX import SummaryWriter
 
 from domid.algos.observers.b_obvisitor_clustering_only import ObVisitorClusteringOnly
-from domid.models.model_dec import ModelDEC
-from domid.trainers.trainer_cluster import TrainerCluster
+from domid.models.model_dec import mk_dec
+from domid.trainers.zoo_trainer import TrainerChainNodeGetter
 
 
 <div class="viewcode-block" id="NodeAlgoBuilderDEC"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_dec.NodeAlgoBuilderDEC">[docs]</a>class NodeAlgoBuilderDEC(NodeAlgoBuilder):
@@ -335,26 +332,30 @@ <h1 id="modules-domid-algos-builder-dec--page-root">Source code for domid.algos.
         zd_dim = args.zd_dim
         d_dim = args.d_dim
         L = args.L
-        pretrain = False
-        if args.pre_tr &gt; 0:
-            pretrain = True
 
-        now = "zd_dim_" + str(zd_dim) + "_lr_" + str(args.lr) + "_" + str(datetime.datetime.now())
-        model = ModelDEC(
+        model = mk_dec()(
             zd_dim=zd_dim,
             d_dim=d_dim,
             device=device,
-            L=L,
             i_c=task.isize.c,
             i_h=task.isize.h,
             i_w=task.isize.w,
-            args=args,
+            bs=args.bs,
+            prior=args.prior,
+            random_batching=args.random_batching,
+            model_method=args.model_method,
+            pre_tr_weight_path=args.pre_tr_weight_path,
+            feat_extract=args.feat_extract,
+        )
+
+        observer = ObVisitorCleanUp(
+            ObVisitorClusteringOnly(exp, MSelOracleVisitor(MSelValPerf(max_es=args.es)), device)
         )
-        observer = ObVisitorCleanUp(ObVisitorClusteringOnly(exp, MSelOracleVisitor(MSelTrLoss(max_es=args.es)), device))
-        writer = SummaryWriter(logdir="debug/" + now)
-        trainer = TrainerCluster(model, task, observer, device, writer, pretrain=pretrain, aconf=args)
 
-        return trainer</div></div>
+        trainer = TrainerChainNodeGetter(args.trainer)()
+        trainer.init_business(model, task, observer, device, args)
+
+        return trainer, model, observer, device</div></div>
 
 
 <div class="viewcode-block" id="get_node_na"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_dec.get_node_na">[docs]</a>def get_node_na():

docs/build/html/_modules/domid/algos/builder_m2yd.html

@@ -310,14 +310,15 @@
 
   <h1 id="modules-domid-algos-builder-m2yd--page-root">Source code for domid.algos.builder_m2yd</h1><div class="highlight"><pre>
 <span></span>from domainlab.algos.a_algo_builder import NodeAlgoBuilder
-from domainlab.algos.msels.c_msel import MSelTrLoss
 from domainlab.algos.msels.c_msel_oracle import MSelOracleVisitor
+from domainlab.algos.msels.c_msel_val import MSelValPerf
 from domainlab.algos.observers.c_obvisitor_cleanup import ObVisitorCleanUp
-from domainlab.algos.trainers.train_basic import TrainerBasic
 from domainlab.utils.utils_cuda import get_device
 
 from domid.algos.observers.b_obvisitor_clustering import ObVisitorClustering
-from domid.models.model_m2yd import ModelXY2D
+from domid.algos.observers.b_obvisitor_clustering_only import ObVisitorClusteringOnly
+from domid.models.model_m2yd import mk_m2yd
+from domid.trainers.zoo_trainer import TrainerChainNodeGetter
 
 
 <div class="viewcode-block" id="NodeAlgoBuilderM2YD"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_m2yd.NodeAlgoBuilderM2YD">[docs]</a>class NodeAlgoBuilderM2YD(NodeAlgoBuilder):
@@ -328,7 +329,7 @@ <h1 id="modules-domid-algos-builder-m2yd--page-root">Source code for domid.algos
         task = exp.task
         args = exp.args
         device = get_device(args)
-        model = ModelXY2D(
+        model = mk_m2yd()(
             y_dim=len(task.list_str_y),
             list_str_y=task.list_str_y,
             zd_dim=args.zd_dim,
@@ -338,10 +339,16 @@ <h1 id="modules-domid-algos-builder-m2yd--page-root">Source code for domid.algos
             i_h=task.isize.h,
             i_w=task.isize.w,
         )
-        observer = ObVisitorCleanUp(ObVisitorClustering(exp, MSelOracleVisitor(MSelTrLoss(max_es=args.es)), device))
-        trainer = TrainerBasic()
+
+        observer = ObVisitorCleanUp(
+            ObVisitorClusteringOnly(exp, MSelOracleVisitor(MSelValPerf(max_es=args.es)), device)
+        )
+        # FIXME: may need to be ObVisitorClustering instead of ObVisitorClusteringOnly...
+
+        trainer = TrainerChainNodeGetter(args.trainer)()
         trainer.init_business(model, task, observer, device, args)
-        return trainer</div></div>
+
+        return trainer, model, observer, device</div></div>
 
 
 <div class="viewcode-block" id="get_node_na"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_m2yd.get_node_na">[docs]</a>def get_node_na():

docs/build/html/_modules/domid/algos/builder_sdcn.html

@@ -309,18 +309,15 @@
           <article class="md-content__inner md-typeset" role="main">
 
   <h1 id="modules-domid-algos-builder-sdcn--page-root">Source code for domid.algos.builder_sdcn</h1><div class="highlight"><pre>
-<span></span>import datetime
-
-from domainlab.algos.a_algo_builder import NodeAlgoBuilder
-from domainlab.algos.msels.c_msel import MSelTrLoss
+<span></span>from domainlab.algos.a_algo_builder import NodeAlgoBuilder
 from domainlab.algos.msels.c_msel_oracle import MSelOracleVisitor
+from domainlab.algos.msels.c_msel_val import MSelValPerf
 from domainlab.algos.observers.c_obvisitor_cleanup import ObVisitorCleanUp
 from domainlab.utils.utils_cuda import get_device
-from tensorboardX import SummaryWriter
 
 from domid.algos.observers.b_obvisitor_clustering_only import ObVisitorClusteringOnly
-from domid.models.model_sdcn import ModelSDCN
-from domid.trainers.trainer_sdcn import TrainerCluster
+from domid.models.model_sdcn import mk_sdcn
+from domid.trainers.zoo_trainer import TrainerChainNodeGetter
 
 
 <div class="viewcode-block" id="NodeAlgoBuilderSDCN"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_sdcn.NodeAlgoBuilderSDCN">[docs]</a>class NodeAlgoBuilderSDCN(NodeAlgoBuilder):
@@ -336,26 +333,29 @@ <h1 id="modules-domid-algos-builder-sdcn--page-root">Source code for domid.algos
         zd_dim = args.zd_dim
         d_dim = args.d_dim
         L = args.L
-        pretrain = False
-        if args.pre_tr &gt; 0:
-            pretrain = True
-
-        now = "zd_dim_" + str(zd_dim) + "_lr_" + str(args.lr) + "_" + str(datetime.datetime.now())
-        model = ModelSDCN(
+        model = mk_sdcn()(
             zd_dim=zd_dim,
             d_dim=d_dim,
             device=device,
-            L=L,
             i_c=task.isize.c,
             i_h=task.isize.h,
             i_w=task.isize.w,
-            args=args,
+            bs=args.bs,
+            task=args.task,
+            prior=args.prior,
+            random_batching=args.random_batching,
+            model_method=args.model_method,
+            pre_tr_weight_path=args.pre_tr_weight_path,
+            feat_extract=args.feat_extract,
+        )
+
+        observer = ObVisitorCleanUp(
+            ObVisitorClusteringOnly(exp, MSelOracleVisitor(MSelValPerf(max_es=args.es)), device)
         )
-        observer = ObVisitorCleanUp(ObVisitorClusteringOnly(exp, MSelOracleVisitor(MSelTrLoss(max_es=args.es)), device))
-        writer = SummaryWriter(logdir="debug/" + now)
-        trainer = TrainerCluster(model, task, observer, device, writer, pretrain=pretrain, aconf=args)
+        trainer = TrainerChainNodeGetter(args.trainer)()
+        trainer.init_business(model, task, observer, device, args)
 
-        return trainer</div></div>
+        return trainer, model, observer, device</div></div>
 
 
 <div class="viewcode-block" id="get_node_na"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_sdcn.get_node_na">[docs]</a>def get_node_na():

docs/build/html/_modules/domid/algos/builder_vade.html

@@ -309,18 +309,15 @@
           <article class="md-content__inner md-typeset" role="main">
 
   <h1 id="modules-domid-algos-builder-vade--page-root">Source code for domid.algos.builder_vade</h1><div class="highlight"><pre>
-<span></span>import datetime
-
-from domainlab.algos.a_algo_builder import NodeAlgoBuilder
-from domainlab.algos.msels.c_msel import MSelTrLoss
+<span></span>from domainlab.algos.a_algo_builder import NodeAlgoBuilder
 from domainlab.algos.msels.c_msel_oracle import MSelOracleVisitor
+from domainlab.algos.msels.c_msel_val import MSelValPerf
 from domainlab.algos.observers.c_obvisitor_cleanup import ObVisitorCleanUp
 from domainlab.utils.utils_cuda import get_device
-from tensorboardX import SummaryWriter
 
 from domid.algos.observers.b_obvisitor_clustering_only import ObVisitorClusteringOnly
-from domid.models.model_vade import ModelVaDE
-from domid.trainers.trainer_cluster import TrainerCluster
+from domid.models.model_vade import mk_vade
+from domid.trainers.zoo_trainer import TrainerChainNodeGetter
 
 
 <div class="viewcode-block" id="NodeAlgoBuilderVaDE"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_vade.NodeAlgoBuilderVaDE">[docs]</a>class NodeAlgoBuilderVaDE(NodeAlgoBuilder):
@@ -336,26 +333,32 @@ <h1 id="modules-domid-algos-builder-vade--page-root">Source code for domid.algos
         zd_dim = args.zd_dim
         d_dim = args.d_dim
         L = args.L
-        pretrain = False
-        if args.pre_tr &gt; 0:
-            pretrain = True
 
-        now = "zd_dim_" + str(zd_dim) + "_lr_" + str(args.lr) + "_" + str(datetime.datetime.now())
-        model = ModelVaDE(
+        model = mk_vade()(
             zd_dim=zd_dim,
             d_dim=d_dim,
             device=device,
-            L=L,
             i_c=task.isize.c,
             i_h=task.isize.h,
             i_w=task.isize.w,
-            args=args,
+            bs=args.bs,
+            L=L,
+            dim_inject_y=args.dim_inject_y,
+            prior=args.prior,
+            random_batching=args.random_batching,
+            model_method=args.model_method,
+            pre_tr_weight_path=args.pre_tr_weight_path,
+            feat_extract=args.feat_extract,
         )
-        observer = ObVisitorCleanUp(ObVisitorClusteringOnly(exp, MSelOracleVisitor(MSelTrLoss(max_es=args.es)), device))
-        writer = SummaryWriter(logdir="debug/" + now)
-        trainer = TrainerCluster(model, task, observer, device, writer, pretrain=pretrain, aconf=args)
 
-        return trainer</div></div>
+        observer = ObVisitorCleanUp(
+            ObVisitorClusteringOnly(exp, MSelOracleVisitor(MSelValPerf(max_es=args.es)), device)
+        )
+
+        trainer = TrainerChainNodeGetter(args.trainer)()
+        trainer.init_business(model, task, observer, device, args)
+
+        return trainer, model, observer, device</div></div>
 
 
 <div class="viewcode-block" id="get_node_na"><a class="viewcode-back" href="../../../domid.algos.html#domid.algos.builder_vade.get_node_na">[docs]</a>def get_node_na():

docs/build/html/_modules/domid/arg_parser.html

@@ -321,6 +321,7 @@ <h1 id="modules-domid-arg-parser--page-root">Source code for domid.arg_parser</h
     """
     Args for command line definition
     """
+
     parser = arg_parser.mk_parser_main()
     parser.add_argument("--d_dim", type=int, default=7, help="number of domains (or clusters)")
     parser.add_argument("--pre_tr", type=int, default=25, help="number of pretraining epochs")
@@ -332,7 +333,7 @@ <h1 id="modules-domid-arg-parser--page-root">Source code for domid.arg_parser</h
         help="specifies whether binary or continuous-valued input data. Input either 'Bern' for Bernoulli or 'Gaus' for Gaussian prior distribution for the data.",
     )
     parser.add_argument(
-        "--model",
+        "--model_method",
         type=str,
         default="linear",
         help="specify 'linear' for a fully-connected or 'cnn' for a convolutional model architecture",
@@ -370,7 +371,7 @@ <h1 id="modules-domid-arg-parser--page-root">Source code for domid.arg_parser</h
     parser.add_argument("--feat_extract", type=str, default="vae", help="featue extractor method, either vae or ae")
     parser.add_argument(
         "--random_batching",
-        type=bool,
+        action="store_true",
         default=False,
         help="randomization of the samples inside one batch, only used in SDCN",
     )

docs/build/html/_modules/domid/compos/cnn_AE.html

@@ -309,8 +309,7 @@
           <article class="md-content__inner md-typeset" role="main">
 
   <h1 id="modules-domid-compos-cnn-ae--page-root">Source code for domid.compos.cnn_AE</h1><div class="highlight"><pre>
-<span></span>import numpy as np
-import torch
+<span></span>import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
@@ -344,6 +343,13 @@ <h1 id="modules-domid-compos-cnn-ae--page-root">Source code for domid.compos.cnn
         self.bsnorm2 = nn.BatchNorm2d(num_filters[1])
         self.bsnorm3 = nn.BatchNorm2d(num_filters[2])</div>
 
+<div class="viewcode-block" id="ConvolutionalEncoder.get_z"><a class="viewcode-back" href="../../../domid.compos.html#domid.compos.cnn_AE.ConvolutionalEncoder.get_z">[docs]</a>    def get_z(self, x):
+        *_, z = self.forward(x)
+        return z</div>
+
+<div class="viewcode-block" id="ConvolutionalEncoder.get_log_sigma2"><a class="viewcode-back" href="../../../domid.compos.html#domid.compos.cnn_AE.ConvolutionalEncoder.get_log_sigma2">[docs]</a>    def get_log_sigma2(self, x):
+        return None</div>
+
 <div class="viewcode-block" id="ConvolutionalEncoder.forward"><a class="viewcode-back" href="../../../domid.compos.html#domid.compos.cnn_AE.ConvolutionalEncoder.forward">[docs]</a>    def forward(self, x):
         """
         :param x: input data

docs/build/html/_modules/domid/compos/cnn_VAE.html

@@ -309,8 +309,7 @@
           <article class="md-content__inner md-typeset" role="main">
 
   <h1 id="modules-domid-compos-cnn-vae--page-root">Source code for domid.compos.cnn_VAE</h1><div class="highlight"><pre>
-<span></span>import numpy as np
-import torch.nn as nn
+<span></span>import torch.nn as nn
 
 from domid.compos.VAE_blocks import UnFlatten, get_output_shape
 
@@ -341,6 +340,14 @@ <h1 id="modules-domid-compos-cnn-vae--page-root">Source code for domid.compos.cn
         self.mu_layer = nn.Linear(self.h_dim, zd_dim)
         self.log_sigma2_layer = nn.Linear(self.h_dim, zd_dim)</div>
 
+<div class="viewcode-block" id="ConvolutionalEncoder.get_z"><a class="viewcode-back" href="../../../domid.compos.html#domid.compos.cnn_VAE.ConvolutionalEncoder.get_z">[docs]</a>    def get_z(self, x):
+        mu, _ = self.forward(x)
+        return mu</div>
+
+<div class="viewcode-block" id="ConvolutionalEncoder.get_log_sigma2"><a class="viewcode-back" href="../../../domid.compos.html#domid.compos.cnn_VAE.ConvolutionalEncoder.get_log_sigma2">[docs]</a>    def get_log_sigma2(self, x):
+        _, log_sigma2 = self.forward(x)
+        return log_sigma2</div>
+
 <div class="viewcode-block" id="ConvolutionalEncoder.forward"><a class="viewcode-back" href="../../../domid.compos.html#domid.compos.cnn_VAE.ConvolutionalEncoder.forward">[docs]</a>    def forward(self, x):
         """
         :param x: input data