diff --git a/README.md b/README.md index 38e0821..858fea7 100755 --- a/README.md +++ b/README.md @@ -190,6 +190,7 @@ Below are settings that override the default launch arguments. Some of these req - For example, `10.0.0.1:8008/gradio` will have the web UI only accept connections through `10.0.0.1`, at the path `/gradio` * `Public Share Gradio`: Tells Gradio to generate a public URL for the web UI. Ignored if specifying a path through the `Listen` setting. * `Check for Updates`: checks for updates on page load and notifies in console. Only works if you pulled this repo from a gitea instance. +* `Only Load Models Locally`: enforces offline mode for loading models. This is the equivalent of setting the env var: `TRANSFORMERS_OFFLINE` * `Low VRAM`: disables optimizations in TorToiSe that increases VRAM consumption. Suggested if your GPU has under 6GiB. * `Embed Output Metadata`: enables embedding the settings and latents used to generate that audio clip inside that audio clip. Metadata is stored as a JSON string in the `lyrics` tag. * `Slimmer Computed Latents`: falls back to the original, 12.9KiB way of storing latents (without the extra bits required for using the CVVP model). diff --git a/app.py b/app.py index 74048db..c0a0422 100755 --- a/app.py +++ b/app.py @@ -322,11 +322,12 @@ def check_for_updates(): def update_voices(): return gr.Dropdown.update(choices=sorted(os.listdir("./tortoise/voices")) + ["microphone"]) -def export_exec_settings( share, listen, check_for_updates, low_vram, embed_output_metadata, latents_lean_and_mean, cond_latent_max_chunk_size, sample_batch_size, concurrency_count ): +def export_exec_settings( share, listen, check_for_updates, models_from_local_only, low_vram, embed_output_metadata, latents_lean_and_mean, cond_latent_max_chunk_size, sample_batch_size, concurrency_count ): args.share = share args.listen = listen args.low_vram = low_vram args.check_for_updates = check_for_updates + args.models_from_local_only = models_from_local_only args.cond_latent_max_chunk_size = cond_latent_max_chunk_size args.sample_batch_size = sample_batch_size args.embed_output_metadata = embed_output_metadata @@ -338,6 +339,7 @@ def export_exec_settings( share, listen, check_for_updates, low_vram, embed_outp 'listen': args.listen, 'low-vram':args.low_vram, 'check-for-updates':args.check_for_updates, + 'models-from-local-only':args.models_from_local_only, 'cond-latent-max-chunk-size': args.cond_latent_max_chunk_size, 'sample-batch-size': args.sample_batch_size, 'embed-output-metadata': args.embed_output_metadata, @@ -353,6 +355,7 @@ def setup_args(): 'share': False, 'listen': None, 'check-for-updates': False, + 'models-from-local-only': False, 'low-vram': False, 'sample-batch-size': None, 'embed-output-metadata': True, @@ -371,6 +374,7 @@ def setup_args(): parser.add_argument("--share", action='store_true', default=default_arguments['share'], help="Lets Gradio return a public URL to use anywhere") parser.add_argument("--listen", default=default_arguments['listen'], help="Path for Gradio to listen on") parser.add_argument("--check-for-updates", action='store_true', default=default_arguments['check-for-updates'], help="Checks for update on startup") + parser.add_argument("--models-from-local-only", action='store_true', default=default_arguments['models-from-local-only'], help="Only loads models from disk, does not check for updates for models") parser.add_argument("--low-vram", action='store_true', default=default_arguments['low-vram'], help="Disables some optimizations that increases VRAM usage") parser.add_argument("--no-embed-output-metadata", action='store_false', default=not default_arguments['embed-output-metadata'], help="Disables embedding output metadata into resulting WAV files for easily fetching its settings used with the web UI (data is stored in the lyrics metadata tag)") parser.add_argument("--latents-lean-and-mean", action='store_true', default=default_arguments['latents-lean-and-mean'], help="Exports the bare essentials for latents.") @@ -416,6 +420,9 @@ def setup_gradio(): gradio.utils.log_feature_analytics = noop(gradio.utils.log_feature_analytics) #gradio.utils.get_local_ip_address = noop(gradio.utils.get_local_ip_address, 'localhost') + if args.models_from_local_only: + os.environ['TRANSFORMERS_OFFLINE']='1' + with gr.Blocks() as webui: with gr.Tab("Generate"): with gr.Row(): @@ -513,7 +520,8 @@ def setup_gradio(): with gr.Box(): exec_arg_listen = gr.Textbox(label="Listen", value=args.listen, placeholder="127.0.0.1:7860/") exec_arg_share = gr.Checkbox(label="Public Share Gradio", value=args.share) - exec_check_for_updates = gr.Checkbox(label="Check For Updates", value=args.check_for_updates) + exec_arg_check_for_updates = gr.Checkbox(label="Check For Updates", value=args.check_for_updates) + exec_arg_models_from_local_only = gr.Checkbox(label="Only Load Models Locally", value=args.models_from_local_only) exec_arg_low_vram = gr.Checkbox(label="Low VRAM", value=args.low_vram) exec_arg_embed_output_metadata = gr.Checkbox(label="Embed Output Metadata", value=args.embed_output_metadata) exec_arg_latents_lean_and_mean = gr.Checkbox(label="Slimmer Computed Latents", value=args.latents_lean_and_mean) @@ -527,7 +535,7 @@ def setup_gradio(): check_updates_now = gr.Button(value="Check for Updates") - exec_inputs = [exec_arg_share, exec_arg_listen, exec_check_for_updates, exec_arg_low_vram, exec_arg_embed_output_metadata, exec_arg_latents_lean_and_mean, exec_arg_cond_latent_max_chunk_size, exec_arg_sample_batch_size, exec_arg_concurrency_count] + exec_inputs = [exec_arg_share, exec_arg_listen, exec_arg_check_for_updates, exec_arg_models_from_local_only, exec_arg_low_vram, exec_arg_embed_output_metadata, exec_arg_latents_lean_and_mean, exec_arg_cond_latent_max_chunk_size, exec_arg_sample_batch_size, exec_arg_concurrency_count] for i in exec_inputs: i.change( diff --git a/tortoise/api.py b/tortoise/api.py index cd2c384..fab533b 100755 --- a/tortoise/api.py +++ b/tortoise/api.py @@ -626,6 +626,8 @@ class TextToSpeech: else: res = wav_candidates[0] + gc.collect() + if return_deterministic_state: return res, (deterministic_seed, text, voice_samples, conditioning_latents) else: