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gradio finetune fix last per step and add note (#284)

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* fix path

* change name

* change name

* fix path

* fix last per steps and add notes

* change order tab add note in vocab check tab

* add note in reduse checkpoint tab

* note in reduse checkpoint tab update
This commit is contained in:
lpscr
2024-10-26 12:57:04 +03:00
committed by GitHub
parent 6c623447b8
commit c1a9986a15
1 changed files with 30 additions and 18 deletions
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48
src/f5_tts/train/finetune_gradio.py
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@@ -663,12 +663,14 @@ def calculate_train(
num_warmup_updates = int(samples * 0.05)
save_per_updates = int(samples * 0.10)
last_per_steps = int(save_per_updates * 5)
last_per_steps = int(save_per_updates * 0.25)
max_samples = (lambda num: num + 1 if num % 2 != 0 else num)(max_samples)
num_warmup_updates = (lambda num: num + 1 if num % 2 != 0 else num)(num_warmup_updates)
save_per_updates = (lambda num: num + 1 if num % 2 != 0 else num)(save_per_updates)
last_per_steps = (lambda num: num + 1 if num % 2 != 0 else num)(last_per_steps)
if last_per_steps <= 0:
last_per_steps = 2
total_hours = hours
mel_hop_length = 256
@@ -1046,7 +1048,19 @@ for tutorial and updates check here (https://github.com/SWivid/F5-TTS/discussion
fn=get_random_sample_prepare, inputs=[cm_project], outputs=[random_text_prepare, random_audio_prepare]
)
with gr.TabItem("vocab check"):
gr.Markdown("""```plaintext
check the vocabulary for fine-tuning Emilia_ZH_EN to ensure all symbols are included. for finetune new language
```""")
check_button = gr.Button("check vocab")
txt_info_check = gr.Text(label="info", value="")
check_button.click(fn=vocab_check, inputs=[cm_project], outputs=[txt_info_check])
with gr.TabItem("train Data"):
gr.Markdown("""```plaintext
The auto-setting is still experimental. Please make sure that the epochs , save per updates , and last per steps are set correctly, or change them manually as needed.
If you encounter a memory error, try reducing the batch size per GPU to a smaller number.
```""")
with gr.Row():
bt_calculate = bt_create = gr.Button("Auto Settings")
lb_samples = gr.Label(label="samples")
@@ -1136,23 +1150,6 @@ for tutorial and updates check here (https://github.com/SWivid/F5-TTS/discussion
check_finetune, inputs=[ch_finetune], outputs=[file_checkpoint_train, tokenizer_file, tokenizer_type]
)
with gr.TabItem("reduse checkpoint"):
txt_path_checkpoint = gr.Text(label="path checkpoint :")
txt_path_checkpoint_small = gr.Text(label="path output :")
ch_safetensors = gr.Checkbox(label="safetensors", value="")
txt_info_reduse = gr.Text(label="info", value="")
reduse_button = gr.Button("reduse")
reduse_button.click(
fn=extract_and_save_ema_model,
inputs=[txt_path_checkpoint, txt_path_checkpoint_small, ch_safetensors],
outputs=[txt_info_reduse],
)
with gr.TabItem("vocab check"):
check_button = gr.Button("check vocab")
txt_info_check = gr.Text(label="info", value="")
check_button.click(fn=vocab_check, inputs=[cm_project], outputs=[txt_info_check])
with gr.TabItem("test model"):
exp_name = gr.Radio(label="Model", choices=["F5-TTS", "E2-TTS"], value="F5-TTS")
list_checkpoints, checkpoint_select = get_checkpoints_project(projects_selelect, False)
@@ -1189,6 +1186,21 @@ for tutorial and updates check here (https://github.com/SWivid/F5-TTS/discussion
bt_checkpoint_refresh.click(fn=get_checkpoints_project, inputs=[cm_project], outputs=[cm_checkpoint])
cm_project.change(fn=get_checkpoints_project, inputs=[cm_project], outputs=[cm_checkpoint])
with gr.TabItem("reduse checkpoint"):
gr.Markdown("""```plaintext
Reduce the model size from 5GB to 1.3GB. The new checkpoint can be used for inference or fine-tuning afterward, but it cannot be used to continue training..
```""")
txt_path_checkpoint = gr.Text(label="path checkpoint :")
txt_path_checkpoint_small = gr.Text(label="path output :")
ch_safetensors = gr.Checkbox(label="safetensors", value="")
txt_info_reduse = gr.Text(label="info", value="")
reduse_button = gr.Button("reduse")
reduse_button.click(
fn=extract_and_save_ema_model,
inputs=[txt_path_checkpoint, txt_path_checkpoint_small, ch_safetensors],
outputs=[txt_info_reduse],
)
with gr.TabItem("system info"):
output_box = gr.Textbox(label="GPU and CPU Information", lines=20)