Persist ACE-Step XL-SFT quality defaults
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Mikei386
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"""Output and automation controls for generation advanced settings."""
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from typing import Any
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import gradio as gr
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from acestep.ui.gradio.i18n import t
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_MP3_BITRATE_CHOICES = [("128 kbps", "128k"), ("192 kbps", "192k"), ("256 kbps", "256k"), ("320 kbps", "320k")]
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_MP3_SAMPLE_RATE_CHOICES = [("48 kHz", 48000), ("44.1 kHz", 44100)]
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def _update_mp3_control_visibility(audio_format: str, service_mode: bool = False):
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"""Return visibility and interactivity updates for MP3-only controls."""
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visible = audio_format == "mp3"
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interactive = visible and not service_mode
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return (
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gr.update(visible=visible),
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gr.update(choices=_MP3_BITRATE_CHOICES, visible=visible, interactive=interactive),
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gr.update(choices=_MP3_SAMPLE_RATE_CHOICES, visible=visible, interactive=interactive),
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)
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def build_output_controls(
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service_pre_initialized: bool,
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service_mode: bool,
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init_params: dict[str, Any] | None,
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) -> dict[str, Any]:
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"""Create audio-output and post-processing controls for advanced settings.
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Args:
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service_pre_initialized: Whether existing init params should prefill values.
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service_mode: Whether the UI is running in service mode (disables some controls).
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init_params: Optional startup state containing persisted output values.
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Returns:
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A component map containing format, scoring, normalization, and latent controls.
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"""
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params = init_params or {}
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# Keep the master lossless. MP3 is only an optional sharing export.
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initial_audio_format = params.get("audio_format", "flac")
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initial_mp3_visible = initial_audio_format == "mp3"
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with gr.Accordion(t("generation.advanced_output_section"), open=False, elem_classes=["has-info-container"]):
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with gr.Row():
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with gr.Column(scale=1):
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audio_format = gr.Dropdown(
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choices=[
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("FLAC", "flac"),
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("MP3", "mp3"),
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("Opus", "opus"),
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("AAC", "aac"),
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("WAV (16-bit)", "wav"),
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("WAV (32-bit Float)", "wav32"),
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],
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value=initial_audio_format,
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label=t("generation.audio_format_label"),
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info=t("generation.audio_format_info"),
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elem_id="acestep-audio-format",
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elem_classes=["has-info-container"],
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interactive=not service_mode,
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)
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with gr.Row(visible=initial_mp3_visible) as mp3_controls_row:
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mp3_bitrate = gr.Dropdown(
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choices=[
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("128 kbps", "128k"),
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("192 kbps", "192k"),
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("256 kbps", "256k"),
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("320 kbps", "320k"),
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],
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value=params.get("mp3_bitrate", "320k"),
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label=t("generation.mp3_bitrate_label"),
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info=t("generation.mp3_bitrate_info"),
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elem_id="acestep-mp3-bitrate",
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elem_classes=["has-info-container"],
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visible=initial_mp3_visible,
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interactive=initial_mp3_visible and not service_mode,
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scale=1,
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)
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mp3_sample_rate = gr.Dropdown(
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choices=[
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("48 kHz", 48000),
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("44.1 kHz", 44100),
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],
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value=params.get("mp3_sample_rate", 48000),
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label=t("generation.mp3_sample_rate_label"),
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info=t("generation.mp3_sample_rate_info"),
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elem_id="acestep-mp3-sample-rate",
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elem_classes=["has-info-container"],
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visible=initial_mp3_visible,
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interactive=initial_mp3_visible and not service_mode,
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scale=1,
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)
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with gr.Column(scale=1):
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score_scale = gr.Slider(
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minimum=0.01,
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maximum=1.0,
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value=0.5,
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step=0.01,
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label=t("generation.score_sensitivity_label"),
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info=t("generation.score_sensitivity_info"),
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elem_id="acestep-score-scale",
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elem_classes=["has-info-container"],
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scale=1,
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visible=not service_mode,
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)
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audio_format.change(
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fn=lambda value: _update_mp3_control_visibility(value, service_mode),
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inputs=[audio_format],
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outputs=[mp3_controls_row, mp3_bitrate, mp3_sample_rate],
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)
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with gr.Row():
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enable_normalization = gr.Checkbox(
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label=t("generation.enable_normalization"),
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value=params.get("enable_normalization", True) if service_pre_initialized else True,
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info=t("generation.enable_normalization_info"),
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elem_id="acestep-enable-normalization",
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elem_classes=["has-info-container"],
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)
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normalization_db = gr.Slider(
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label=t("generation.normalization_db"),
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minimum=-10.0,
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maximum=0.0,
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step=0.1,
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value=params.get("normalization_db", -1.0) if service_pre_initialized else -1.0,
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info=t("generation.normalization_db_info"),
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elem_id="acestep-normalization-db",
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elem_classes=["has-info-container"],
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)
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with gr.Row():
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fade_in_duration = gr.Slider(
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label=t("generation.fade_in_duration"),
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minimum=0.0,
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maximum=10.0,
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step=0.1,
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value=params.get("fade_in_duration", 0.0) if service_pre_initialized else 0.0,
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info=t("generation.fade_in_duration_info"),
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elem_id="acestep-fade-in-duration",
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elem_classes=["has-info-container"],
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)
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fade_out_duration = gr.Slider(
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label=t("generation.fade_out_duration"),
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minimum=0.0,
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maximum=10.0,
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step=0.1,
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value=params.get("fade_out_duration", 0.0) if service_pre_initialized else 0.0,
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info=t("generation.fade_out_duration_info"),
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elem_id="acestep-fade-out-duration",
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elem_classes=["has-info-container"],
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)
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with gr.Row():
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latent_shift = gr.Slider(
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label=t("generation.latent_shift"),
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minimum=-0.2,
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maximum=0.2,
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step=0.01,
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value=params.get("latent_shift", 0.0) if service_pre_initialized else 0.0,
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info=t("generation.latent_shift_info"),
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elem_id="acestep-latent-shift",
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elem_classes=["has-info-container"],
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)
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latent_rescale = gr.Slider(
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label=t("generation.latent_rescale"),
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minimum=0.5,
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maximum=1.5,
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step=0.01,
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value=params.get("latent_rescale", 1.0) if service_pre_initialized else 1.0,
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info=t("generation.latent_rescale_info"),
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elem_id="acestep-latent-rescale",
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elem_classes=["has-info-container"],
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)
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return {
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"audio_format": audio_format,
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"mp3_controls_row": mp3_controls_row,
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"mp3_bitrate": mp3_bitrate,
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"mp3_sample_rate": mp3_sample_rate,
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"score_scale": score_scale,
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"enable_normalization": enable_normalization,
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"normalization_db": normalization_db,
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"fade_in_duration": fade_in_duration,
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"fade_out_duration": fade_out_duration,
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"latent_shift": latent_shift,
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"latent_rescale": latent_rescale,
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}
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def build_automation_controls(service_mode: bool) -> dict[str, Any]:
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"""Create automation controls for LM batch chunking.
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Args:
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service_mode: Whether the UI is running in service mode (disables some controls).
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Returns:
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A component map containing ``lm_batch_chunk_size``.
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"""
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with gr.Accordion(
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t("generation.advanced_automation_section"),
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open=False,
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elem_classes=["has-info-container"],
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):
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with gr.Row():
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lm_batch_chunk_size = gr.Number(
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label=t("generation.lm_batch_chunk_label"),
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value=8,
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minimum=1,
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maximum=32,
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step=1,
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info=t("generation.lm_batch_chunk_info"),
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scale=1,
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interactive=not service_mode,
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elem_id="acestep-lm-batch-chunk-size",
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elem_classes=["has-info-container"],
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)
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return {"lm_batch_chunk_size": lm_batch_chunk_size}
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