oops

src/utils.py

@@ -153,7 +153,10 @@ def generate(
 
 	# clamp it down for the insane users who want this
 	# it would be wiser to enforce the sample size to the batch size, but this is what the user wants
-	if num_autoregressive_samples < args.sample_batch_size:
+	sample_batch_size = args.sample_batch_size
+	if not sample_batch_size:
+		sample_batch_size = tts.autoregressive_batch_size
+	if num_autoregressive_samples < sample_batch_size:
 		settings['sample_batch_size'] = num_autoregressive_samples
 
 	if delimiter is None:
@@ -493,7 +496,12 @@ def run_training(config_path, verbose=False, buffer_size=8, progress=gr.Progress
 
 				progress(it / float(its), f'[{it}/{its}] {it_rate} Training... {status}')
 
-			if line.find('INFO: [epoch:') >= 0:
+			# it also says Start training from epoch, so it might be better to do that
+			if line.find('INFO: Resuming training from epoch:') >= 0:
+				match = re.findall(r'iter: ([\d,]+)', line)
+				if match and len(match) > 0:
+					it = int(match[0].replace(",", ""))
+			elif line.find('INFO: [epoch:') >= 0:
 				# easily rip out our stats...
 				match = re.findall(r'\b([a-z_0-9]+?)\b: ([0-9]\.[0-9]+?e[+-]\d+)\b', line)
 				if match and len(match) > 0:

src/webui.py

@@ -288,7 +288,7 @@ def setup_gradio():
 					seed = gr.Number(value=0, precision=0, label="Seed")
 
 					preset = gr.Radio( ["Ultra Fast", "Fast", "Standard", "High Quality"], label="Preset", type="value" )
-					num_autoregressive_samples = gr.Slider(value=128, minimum=0, maximum=512, step=1, label="Samples")
+					num_autoregressive_samples = gr.Slider(value=128, minimum=2, maximum=512, step=1, label="Samples")
 					diffusion_iterations = gr.Slider(value=128, minimum=0, maximum=512, step=1, label="Iterations")
 
 					temperature = gr.Slider(value=0.2, minimum=0, maximum=1, step=0.1, label="Temperature")