diff --git a/README.md b/README.md index f32d490..5ffc52b 100644 --- a/README.md +++ b/README.md @@ -133,7 +133,7 @@ Any file listed in the list models output can be specified (with file extension) ```sh usage: audio-separator [-h] [-v] [-d] [-e] [-l] [--log_level LOG_LEVEL] [-m MODEL_FILENAME] [--output_format OUTPUT_FORMAT] [--output_dir OUTPUT_DIR] [--model_file_dir MODEL_FILE_DIR] [--invert_spect] - [--normalization NORMALIZATION] [--single_stem SINGLE_STEM] [--sample_rate SAMPLE_RATE] [--mdx_segment_size MDX_SEGMENT_SIZE] [--mdx_overlap MDX_OVERLAP] [--mdx_batch_size MDX_BATCH_SIZE] + [--normalization NORMALIZATION] [--single_stem SINGLE_STEM] [--sample_rate SAMPLE_RATE] [--use_autocast] [--mdx_segment_size MDX_SEGMENT_SIZE] [--mdx_overlap MDX_OVERLAP] [--mdx_batch_size MDX_BATCH_SIZE] [--mdx_hop_length MDX_HOP_LENGTH] [--mdx_enable_denoise] [--vr_batch_size VR_BATCH_SIZE] [--vr_window_size VR_WINDOW_SIZE] [--vr_aggression VR_AGGRESSION] [--vr_enable_tta] [--vr_high_end_process] [--vr_enable_post_process] [--vr_post_process_threshold VR_POST_PROCESS_THRESHOLD] [--demucs_segment_size DEMUCS_SEGMENT_SIZE] [--demucs_shifts DEMUCS_SHIFTS] [--demucs_overlap DEMUCS_OVERLAP] [--demucs_segments_enabled DEMUCS_SEGMENTS_ENABLED] [--mdxc_segment_size MDXC_SEGMENT_SIZE] [--mdxc_override_model_segment_size] @@ -166,6 +166,7 @@ Common Separation Parameters: --normalization NORMALIZATION value by which to multiply the amplitude of the output files (default: 0.9). Example: --normalization=0.7 --single_stem SINGLE_STEM output only single stem, e.g. Instrumental, Vocals, Drums, Bass, Guitar, Piano, Other. Example: --single_stem=Instrumental --sample_rate SAMPLE_RATE set the sample rate of the output audio (default: 44100). Example: --sample_rate=44100 + --use_autocast use PyTorch autocast for faster inference (default: False). Do not use for CPU inference. Example: --use_autocast MDX Architecture Parameters: --mdx_segment_size MDX_SEGMENT_SIZE larger consumes more resources, but may give better results (default: 256). Example: --mdx_segment_size=256 @@ -315,6 +316,7 @@ output_file_paths_6 = separator.separate('audio3.wav') - invert_using_spec: (Optional) Flag to invert using spectrogram. Default: False - sample_rate: (Optional) Set the sample rate of the output audio. Default: 44100 - use_soundfile: (Optional) Use soundfile for output writing, can solve OOM issues, especially on longer audio. +- use_autocast: (Optional) Flag to use PyTorch autocast for faster inference.　Do not use for CPU inference. Default: False - mdx_params: (Optional) MDX Architecture Specific Attributes & Defaults. Default: {"hop_length": 1024, "segment_size": 256, "overlap": 0.25, "batch_size": 1} - vr_params: (Optional) VR Architecture Specific Attributes & Defaults. Default: {"batch_size": 1, "window_size": 512, "aggression": 5, "enable_tta": False, "enable_post_process": False, "post_process_threshold": 0.2, "high_end_process": False} - demucs_params: (Optional) VR Architecture Specific Attributes & Defaults. {"segment_size": "Default", "shifts": 2, "overlap": 0.25, "segments_enabled": True} diff --git a/audio_separator/separator/architectures/mdxc_separator.py b/audio_separator/separator/architectures/mdxc_separator.py index 72d36cb..36bfbd2 100644 --- a/audio_separator/separator/architectures/mdxc_separator.py +++ b/audio_separator/separator/architectures/mdxc_separator.py @@ -239,7 +239,6 @@ def demix(self, mix: np.ndarray) -> dict: # Transfer to the weighting plate for the same device as the other tensors window = window.to(device) - # with torch.cuda.amp.autocast(): with torch.no_grad(): req_shape = (len(self.model_data_cfgdict.training.instruments),) + tuple(mix.shape) result = torch.zeros(req_shape, dtype=torch.float32).to(device) diff --git a/audio_separator/separator/separator.py b/audio_separator/separator/separator.py index f3a3710..41c6859 100644 --- a/audio_separator/separator/separator.py +++ b/audio_separator/separator/separator.py @@ -15,6 +15,7 @@ import yaml import requests import torch +import torch.amp.autocast_mode as autocast_mode import onnxruntime as ort from tqdm import tqdm @@ -43,6 +44,7 @@ class Separator: invert_using_spec (bool): Flag to invert using spectrogram. sample_rate (int): The sample rate of the audio. use_soundfile (bool): Use soundfile for audio writing, can solve OOM issues. + use_autocast (bool): Flag to use PyTorch autocast for faster inference. MDX Architecture Specific Attributes: hop_length (int): The hop length for STFT. @@ -78,6 +80,7 @@ def __init__( invert_using_spec=False, sample_rate=44100, use_soundfile=False, + use_autocast=False, mdx_params={"hop_length": 1024, "segment_size": 256, "overlap": 0.25, "batch_size": 1, "enable_denoise": False}, vr_params={"batch_size": 1, "window_size": 512, "aggression": 5, "enable_tta": False, "enable_post_process": False, "post_process_threshold": 0.2, "high_end_process": False}, demucs_params={"segment_size": "Default", "shifts": 2, "overlap": 0.25, "segments_enabled": True}, @@ -150,6 +153,7 @@ def __init__( raise ValueError("The sample rate must be a non-zero whole number. Please provide a valid integer.") self.use_soundfile = use_soundfile + self.use_autocast = use_autocast # These are parameters which users may want to configure so we expose them to the top-level Separator class, # even though they are specific to a single model architecture @@ -737,6 +741,9 @@ def separate(self, audio_file_path): Returns: - output_files (list of str): A list containing the paths to the separated audio stem files. """ + if not (self.torch_device and self.model_instance): + raise ValueError("Initialization failed or model not loaded. Please load a model before attempting to separate.") + # Starting the separation process self.logger.info(f"Starting separation process for audio_file_path: {audio_file_path}") separate_start_time = time.perf_counter() @@ -744,8 +751,15 @@ def separate(self, audio_file_path): self.logger.debug(f"Normalization threshold set to {self.normalization_threshold}, waveform will lowered to this max amplitude to avoid clipping.") self.logger.debug(f"Amplification threshold set to {self.amplification_threshold}, waveform will scaled up to this max amplitude if below it.") - # Run separation method for the loaded model - output_files = self.model_instance.separate(audio_file_path) + # Run separation method for the loaded model with autocast enabled if supported by the device. + output_files = None + if self.use_autocast and autocast_mode.is_autocast_available(self.torch_device.type): + self.logger.debug("Autocast available.") + with autocast_mode.autocast(self.torch_device.type): + output_files = self.model_instance.separate(audio_file_path) + else: + self.logger.debug("Autocast unavailable.") + output_files = self.model_instance.separate(audio_file_path) # Clear GPU cache to free up memory self.model_instance.clear_gpu_cache() diff --git a/audio_separator/utils/cli.py b/audio_separator/utils/cli.py index 14f007d..7e33f4a 100755 --- a/audio_separator/utils/cli.py +++ b/audio_separator/utils/cli.py @@ -55,6 +55,7 @@ def main(): single_stem_help = "output only single stem, e.g. Instrumental, Vocals, Drums, Bass, Guitar, Piano, Other. Example: --single_stem=Instrumental" sample_rate_help = "modify the sample rate of the output audio (default: %(default)s). Example: --sample_rate=44100" use_soundfile_help = "Use soundfile to write audio output (default: %(default)s). Example: --use_soundfile" + use_autocast_help = "use PyTorch autocast for faster inference (default: %(default)s). Do not use for CPU inference. Example: --use_autocast" common_params = parser.add_argument_group("Common Separation Parameters") common_params.add_argument("--invert_spect", action="store_true", help=invert_spect_help) @@ -63,6 +64,7 @@ def main(): common_params.add_argument("--single_stem", default=None, help=single_stem_help) common_params.add_argument("--sample_rate", type=int, default=44100, help=sample_rate_help) common_params.add_argument("--use_soundfile", action="store_true", help=use_soundfile_help) + common_params.add_argument("--use_autocast", action="store_true", help=use_autocast_help) mdx_segment_size_help = "larger consumes more resources, but may give better results (default: %(default)s). Example: --mdx_segment_size=256" mdx_overlap_help = "amount of overlap between prediction windows, 0.001-0.999. higher is better but slower (default: %(default)s). Example: --mdx_overlap=0.25" @@ -163,6 +165,8 @@ def main(): output_single_stem=args.single_stem, invert_using_spec=args.invert_spect, sample_rate=args.sample_rate, + use_soundfile=args.use_soundfile, + use_autocast=args.use_autocast, mdx_params={ "hop_length": args.mdx_hop_length, "segment_size": args.mdx_segment_size, diff --git a/poetry.lock b/poetry.lock index c9b5d27..ced81eb 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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