Update Semibin 2.0.2 to 2.2.0

tools/semibin/bin.xml

@@ -11,11 +11,15 @@
     <command detect_errors="exit_code"><![CDATA[
 #import re
 @FASTA_FILES@
+
+#if $mod.select == 'history':
+python '$__tool_directory__/convert.py' '$mod.model' &&
+
 SemiBin2 bin
     --input-fasta 'contigs.$input_fasta.ext'
     --data '$data'
 #if $mod.select == 'history'
-    --model '$mod.model'
+    --model 'model.pt'
 #else
     --environment '$mod.environment'
 #end if
@@ -31,6 +35,10 @@ SemiBin2 bin
     --compression none
     @MIN_LEN@
     --orf-finder '$orf_finder'
+
+#if $mod.select == 'history'
+&&
+rm 'model.pt'
     ]]></command>
     <inputs>
         <expand macro="mode_fasta"/>
@@ -44,7 +52,7 @@ SemiBin2 bin
                 <expand macro="environment"/>
             </when>
             <when value="history">
-                <param argument="--model" type="data" format="h5" label="Trained semi-supervised deep learning model"/>
+                <param argument="--model" type="data" format="safetensors" label="Trained semi-supervised deep learning model"/>
             </when>
         </conditional>
         <expand macro="min_len"/>
@@ -78,7 +86,7 @@ SemiBin2 bin
             <param name="data" ftype="csv" value="data.csv"/>
             <conditional name="mod">
                 <param name="select" value="history"/>
-                <param name="model" ftype="h5" value="model.h5"/>
+                <param name="model" ftype="safetensors" location="https://zenodo.org/records/17373295/files/model.safetensors"/>
             </conditional>
             <conditional name="min_len">
                 <param name="method" value="min-len"/>
@@ -141,7 +149,7 @@ SemiBin2 bin
             <param name="data" ftype="csv" value="data.csv"/>
             <conditional name="mod">
                 <param name="select" value="history"/>
-                <param name="model" ftype="h5" value="model.h5"/>
+                <param name="model" ftype="safetensors" location="https://zenodo.org/records/17373295/files/model.safetensors"/>
             </conditional>
             <conditional name="min_len">
                 <param name="method" value="min-len"/>
@@ -172,4 +180,4 @@ Outputs
 
     ]]></help>
     <expand macro="citations"/>
-</tool>
+</tool>

tools/semibin/concatenate_fasta.xml

@@ -63,4 +63,4 @@ Outputs
 
     ]]></help>
     <expand macro="citations"/>
-</tool>
+</tool>

tools/semibin/convert.py

@@ -0,0 +1,94 @@
+import os
+import pickle
+import sys
+
+import torch
+from safetensors.torch import load_file, save_file
+
+# -------------------------------
+# Metadata encoding/decoding
+# -------------------------------
+
+
+def encode_metadata(obj):
+    """
+    Recursively encode Python objects into tensors:
+    - torch.Tensor → leave as-is
+    - dict → recursively encode
+    - list/tuple → convert to dict {0: v0, 1: v1, ...} and encode recursively
+    - other → pickle into uint8 tensor
+    """
+    if isinstance(obj, torch.Tensor):
+        return obj
+    elif isinstance(obj, dict):
+        return {k: encode_metadata(v) for k, v in obj.items()}
+    elif isinstance(obj, (list, tuple)):
+        return {str(i): encode_metadata(v) for i, v in enumerate(obj)}
+    else:
+        data = pickle.dumps(obj)
+        return torch.tensor(list(data), dtype=torch.uint8)
+
+
+def decode_metadata(obj):
+    """
+    Recursively decode tensors back into Python objects.
+    """
+    if isinstance(obj, torch.Tensor):
+        if obj.dtype == torch.uint8:
+            data = bytes(obj.tolist())
+            return pickle.loads(data)
+        return obj
+    elif isinstance(obj, dict):
+        # Convert dicts with all digit keys back to lists
+        if all(k.isdigit() for k in obj.keys()):
+            return [decode_metadata(obj[k]) for k in sorted(obj.keys(), key=int)]
+        else:
+            return {k: decode_metadata(v) for k, v in obj.items()}
+    else:
+        return obj
+
+# -------------------------------
+# Flatten/unflatten for SafeTensors
+# -------------------------------
+
+
+def flatten_dict(d, parent_key='', sep='/'):
+    items = {}
+    for k, v in d.items():
+        new_key = f"{parent_key}{sep}{k}" if parent_key else k
+        if isinstance(v, dict):
+            items.update(flatten_dict(v, new_key, sep=sep))
+        else:
+            items[new_key] = v
+    return items
+
+
+def unflatten_dict(d, sep='/'):
+    result = {}
+    for k, v in d.items():
+        keys = k.split(sep)
+        target = result
+        for key in keys[:-1]:
+            target = target.setdefault(key, {})
+        target[keys[-1]] = v
+    return result
+
+
+# -------------------------------
+# Save .pt as SafeTensors
+# -------------------------------
+
+if __name__ == "__main__":
+    FILE_PATH = sys.argv[1]
+    if FILE_PATH.endswith('.pt'):
+        checkpoint = torch.load("model.pt", map_location="cpu")
+        encoded = encode_metadata(checkpoint)
+        flat = flatten_dict(encoded)
+        save_file(flat, os.path.join(os.path.dirname(sys.argv[1]), "model.safetensors"))
+        print("Saved restorable SafeTensors file!")
+    else:
+        loaded_flat = load_file("model_restorable.safetensors")
+        loaded_nested = unflatten_dict(loaded_flat)
+        restored_checkpoint = decode_metadata(loaded_nested)
+        torch.save(restored_checkpoint, os.path.join(os.path.dirname(sys.argv[1]), "model.pt"))
+        print("Saved restored checkpoint as model_restored.pt!")

tools/semibin/generate_cannot_links.xml

@@ -30,7 +30,6 @@ SemiBin2
 #if $ml_threshold:
     --ml-threshold $ml_threshold
 #end if
-    --cannot-name 'cannot'
     --threads \${GALAXY_SLOTS:-1}
     --processes \${GALAXY_SLOTS:-1}
     ]]></command>
@@ -136,4 +135,4 @@ Outputs
 
     ]]></help>
     <expand macro="citations"/>
-</tool>
+</tool>

tools/semibin/generate_sequence_features.xml

@@ -433,4 +433,4 @@ Outputs
 
     ]]></help>
     <expand macro="citations"/>
-</tool>
+</tool>

tools/semibin/macros.xml

@@ -1,7 +1,7 @@
 <?xml version="1.0"?>
 <macros>
-    <token name="@TOOL_VERSION@">2.1.0</token>
-    <token name="@VERSION_SUFFIX@">1</token>
+    <token name="@TOOL_VERSION@">2.2.0</token>
+    <token name="@VERSION_SUFFIX@">0</token>
     <token name="@PROFILE@">21.01</token>
     <xml name="biotools">
         <xrefs>
@@ -462,7 +462,7 @@ ln -s '$e' '${identifier}.bam' &&
         </collection>
     </xml>
     <xml name="train_output">
-        <data name="model" format="h5" from_work_dir="output/model.h5" label="${tool.name} on ${on_string}: Semi-supervised deep learning model" />
+        <data name="model" format="safetensors" from_work_dir="output/model.safetensors" label="${tool.name} on ${on_string}: Semi-supervised deep learning model" />
     </xml>
     <xml name="cannot_link_output">
         <data name="cannot" format="txt" from_work_dir="output/cannot/cannot.txt" label="${tool.name} on ${on_string}: Cannot-link constraints" />

tools/semibin/train.xml

@@ -55,6 +55,9 @@ SemiBin2 train_semi
     --ratio $min_len.ratio
 #end if
     --orf-finder '$orf_finder'
+
+&& python '$__tool_directory__/convert.py' 'output/model.pt'
+&& rm 'output/model.pt'
     ]]></command>
     <inputs>
         <conditional name="mode">
@@ -101,9 +104,53 @@ SemiBin2 train_semi
             <param name="random_seed" value="0"/>
             <param name="epoches" value="1"/>
             <param name="batch_size" value="2048"/>
-            <output name="model" ftype="h5">
+            <output name="model" ftype="safetensors">
                 <assert_contents>
-                    <has_size value="3119000" delta="2000" />
+                    <has_size value="3115127" delta="2000" />
+                </assert_contents>
+            </output>
+        </test>
+        <test expect_num_outputs="1">
+            <conditional name="mode">
+                <param name="select" value="single"/>
+                <param name="input_fasta" ftype="fasta.bz2" value="input_single.fasta.bz2"/>
+                <param name="data" ftype="csv" value="data.csv"/>
+                <param name="data_split" ftype="csv" value="data_split.csv"/>
+                <param name="cannot_link" ftype="txt" value="cannot.txt"/>
+            </conditional>
+            <conditional name="min_len">
+                <param name="method" value="min-len"/>
+                <param name="min_len" value="2500" />
+            </conditional>
+            <param name="orf_finder" value="prodigal"/>
+            <param name="random_seed" value="0"/>
+            <param name="epoches" value="1"/>
+            <param name="batch_size" value="2048"/>
+            <output name="model" ftype="safetensors">
+                <assert_contents>
+                    <has_size value="3115127" delta="2000" />
+                </assert_contents>
+            </output>
+        </test>
+        <test expect_num_outputs="1">
+            <conditional name="mode">
+                <param name="select" value="single"/>
+                <param name="input_fasta" ftype="fasta.gz" value="input_single.fasta.gz"/>
+                <param name="data" ftype="csv" value="data.csv"/>
+                <param name="data_split" ftype="csv" value="data_split.csv"/>
+                <param name="cannot_link" ftype="txt" value="cannot.txt"/>
+            </conditional>
+            <conditional name="min_len">
+                <param name="method" value="min-len"/>
+                <param name="min_len" value="2500" />
+            </conditional>
+            <param name="orf_finder" value="prodigal"/>
+            <param name="random_seed" value="0"/>
+            <param name="epoches" value="1"/>
+            <param name="batch_size" value="2048"/>
+            <output name="model" ftype="safetensors">
+                <assert_contents>
+                    <has_size value="3115127" delta="2000" />
                 </assert_contents>
             </output>
         </test>
@@ -167,9 +214,9 @@ SemiBin2 train_semi
             <param name="random_seed" value="0"/>
             <param name="epoches" value="20"/>
             <param name="batch_size" value="2048"/>
-            <output name="model" ftype="h5">
+            <output name="model" ftype="safetensors">
                 <assert_contents>
-                    <has_size value="3119000" delta="2000" />
+                    <has_size value="3115127" delta="2000" />
                 </assert_contents>
             </output>
         </test>
@@ -192,4 +239,4 @@ Outputs
 @HELP_MODEL@
     ]]></help>
     <expand macro="citations"/>
-</tool>
+</tool>