refining gather, adding TODOs

TODO.md

@@ -4,12 +4,17 @@
 
 ## Gather
 
-- Add "source" column for tracking provenance
+- Maybe more dataset configurations
+
+## Validate 
+
+A function for validating a dataset for finetuning
 
 ## Fine-tune
 
 - Implement
 
+
 ## Evaluate
 
 - Print more information about the dataset coverage of UCS

pyproject.toml

@@ -13,7 +13,8 @@ dependencies = [
     "tqdm (>=4.67.1,<5.0.0)",
     "platformdirs (>=4.3.8,<5.0.0)",
     "click (>=8.2.1,<9.0.0)",
-    "tabulate (>=0.9.0,<0.10.0)"
+    "tabulate (>=0.9.0,<0.10.0)",
+    "datasets (>=4.0.0,<5.0.0)"
 ]
 
 

ucsinfer/__main__.py

@@ -3,11 +3,14 @@ import sys
 import csv
 import logging
 
+from typing import Generator
+
 import tqdm
 import click
 from tabulate import tabulate, SEPARATING_LINE
 
 from .inference import InferenceContext, load_ucs
+from .gather import build_sentence_class_dataset 
 from .recommend import print_recommendation
 from .util import ffmpeg_description, parse_ucs
 
@@ -117,23 +120,24 @@ def gather(paths, outfile):
     """
     Scan files to build a training dataset at PATH
     
-    The `gather` command walks the directory hierarchy for each path in PATHS 
-    and looks for .wav and .flac files that are named according to the UCS 
-    file naming guidelines, with at least a CatID and FX Name, divided by an 
-    underscore.
-
-    For every file ucsinfer finds that meets this criteria, it creates a record
-    in an output dataset CSV file. The dataset file has two columns: the first
-    is the CatID indicated for the file, and the second is the embedded file 
-    description for the file as returned by ffprobe.
+    The `gather` is used to build a training dataset for finetuning the 
+    selected model. Description sentences and UCS categories are collected from 
+    '.wav' and '.flac' files on-disk that have valid UCS filenames and assigned 
+    CatIDs, and this information is recorded into a HuggingFace dataset.
+    
+    Gather scans the filesystem in two passes: first, the directory tree is 
+    walked by os.walk and a list of filenames that meet the above name criteria 
+    is compiled. After this list is compiled, each file is scanned one-by-one
+    with ffprobe to obtain its "description" metadata; if this isn't present,
+    the parsed 'fxname' of te file becomes the description.
     """
     logger.debug("GATHER mode")
 
     types = ['.wav', '.flac']
-    table = csv.writer(outfile)
 
     logger.debug(f"Loading category list...")
-    catid_list = [cat.catid for cat in load_ucs()]
+    ucs = load_ucs()
+    catid_list = [cat.catid for cat in ucs]
 
     scan_list = []
     for path in paths:
@@ -149,10 +153,18 @@ def gather(paths, outfile):
 
     logger.info(f"Found {len(scan_list)} files to process.")
 
-    for pair in tqdm.tqdm(scan_list, unit='files'):
-        if desc := ffmpeg_description(pair[1]):
-            table.writerow([pair[0], desc])
+    def scan_metadata():
+        for pair in tqdm.tqdm(scan_list, unit='files'):
+            if desc := ffmpeg_description(pair[1]):
+                yield desc, str(pair[0])
+            else:
+                comps = parse_ucs(os.path.basename(pair[1]), catid_list)
+                assert comps
+                yield comps.fx_name, str(pair[0])
 
+    dataset = build_sentence_class_dataset(scan_metadata())
+    dataset.save_to_disk(outfile)
+    
 
 @ucsinfer.command('finetune')
 def finetune():