tweaks

TODO.md

@@ -2,17 +2,15 @@
 
 - Use History when adding catids
 
+
 ## Gather
 
 - Maybe more dataset configurations
 
-## Validate 
-
-A function for validating a dataset for finetuning
 
 ## Fine-tune
 
-- Implement
+- Implement BatchAllTripletLoss
 
 
 ## Evaluate
@@ -22,6 +20,8 @@ A function for validating a dataset for finetuning
 - Print raw output
 - Maybe load everything into a sqlite for slicker reporting
 
+
 ## Utility
 
-- Dataset partitioning
+- Clear caches
+

ucsinfer/__main__.py

@@ -1,9 +1,7 @@
 import os
-import sys
 import csv
 import logging
 
-from typing import Generator
 
 import tqdm
 import click
@@ -26,10 +24,14 @@ logger.addHandler(stream_handler)
 @click.group(epilog="For more information see "
              "<https://git.squad51.us/jamie/ucsinfer>")
 @click.option('--verbose', '-v', flag_value=True, help='Verbose output')
+@click.option('--model', type=str, metavar="<model-name>", 
+              default="paraphrase-multilingual-mpnet-base-v2",
+              show_default=True, 
+              help="Select the sentence_transformer model to use")
 @click.option('--no-model-cache', flag_value=True, 
               help="Don't use local model cache")
 @click.pass_context
-def ucsinfer(ctx, verbose, no_model_cache):
+def ucsinfer(ctx, verbose, no_model_cache, model):
     """
     Tools for applying UCS categories to sounds using large-language Models 
     """
@@ -47,6 +49,12 @@ def ucsinfer(ctx, verbose, no_model_cache):
 
     ctx.ensure_object(dict)
     ctx.obj['model_cache'] = not no_model_cache
+    ctx.obj['model_name'] = model
+
+    if no_model_cache:
+        logger.info("Model cache inhibited by config")
+
+    logger.info("Using model {model}")
 
 
 @ucsinfer.command('recommend')
@@ -54,10 +62,6 @@ def ucsinfer(ctx, verbose, no_model_cache):
               help="Recommend a category for given text instead of reading "
               "from a file")
 @click.argument('paths', nargs=-1, metavar='<paths>')
-@click.option('--model', type=str, metavar="<model-name>", 
-              default="paraphrase-multilingual-mpnet-base-v2",
-              show_default=True, 
-              help="Select the sentence_transformer model to use")
 @click.option('--interactive','-i', flag_value=True, default=False, 
               help="After processing each path in <paths>, prompt for a "
               "recommendation to accept, and then prepend the selection to "
@@ -66,7 +70,7 @@ def ucsinfer(ctx, verbose, no_model_cache):
               help="Skip files that already have a UCS category in their "
               "name.")
 @click.pass_context
-def recommend(ctx, text, paths, model, interactive, skip_ucs):
+def recommend(ctx, text, paths, interactive, skip_ucs):
     """
     Infer a UCS category for a text description
 
@@ -77,7 +81,7 @@ def recommend(ctx, text, paths, model, interactive, skip_ucs):
     of ranked subcategories is printed to the terminal for each PATH.
     """
     logger.debug("RECOMMEND mode")
-    inference_ctx = InferenceContext(model, 
+    inference_ctx = InferenceContext(ctx.obj['model_name'], 
                                      use_cached_model=ctx.obj['model_cache'])
 
     if text is not None:
@@ -167,7 +171,8 @@ def gather(paths, outfile):
     
 
 @ucsinfer.command('finetune')
-def finetune():
+@click.pass_context
+def finetune(ctx):
     """
     Fine-tune a model with training data 
     """
@@ -183,14 +188,10 @@ def finetune():
 @click.option('--no-foley', 'no_foley', flag_value=True, default=False, 
               help="Ignore any data in the set with FOLYProp or FOLYFeet "
               "category")
-@click.option('--model', type=str, metavar="<model-name>", 
-              default="paraphrase-multilingual-mpnet-base-v2",
-              show_default=True, 
-              help="Select the sentence_transformer model to use")
 @click.argument('dataset', type=click.File('r', encoding='utf8'),
                 default='dataset.csv')
 @click.pass_context
-def evaluate(ctx, dataset, offset, limit, model, no_foley):
+def evaluate(ctx, dataset, offset, limit, no_foley):
     """
     Use datasets to evaluate model performance 
 
@@ -211,12 +212,11 @@ def evaluate(ctx, dataset, offset, limit, model, no_foley):
     foley, and so these categories can be excluded with the --no-foley option.
     """
     logger.debug("EVALUATE mode")
-    inference_context = InferenceContext(model, 
+    inference_context = InferenceContext(ctx.obj['model_name'], 
                                          use_cached_model=
                                          ctx.obj['model_cache'])
     reader = csv.reader(dataset)
 
-    logger.info(f"Evaluating model {model}...")
     results = []
     
     if offset > 0: