Introduce code from Rust monorepo. This is a mess

2026-10-17 00:23:14 +00:00 · 2022-02-28 05:43:54 -05:00
parent 921fb49f9a
commit ba326bfcfd
1058 changed files with 192192 additions and 0 deletions
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+# *****************************************************************************
+#  Copyright (c) 2018, NVIDIA CORPORATION.  All rights reserved.
+#
+#  Redistribution and use in source and binary forms, with or without
+#  modification, are permitted provided that the following conditions are met:
+#      * Redistributions of source code must retain the above copyright
+#        notice, this list of conditions and the following disclaimer.
+#      * Redistributions in binary form must reproduce the above copyright
+#        notice, this list of conditions and the following disclaimer in the
+#        documentation and/or other materials provided with the distribution.
+#      * Neither the name of the NVIDIA CORPORATION nor the
+#        names of its contributors may be used to endorse or promote products
+#        derived from this software without specific prior written permission.
+#
+#  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+#  AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+#  IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+#  ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
+#  DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+#  (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+#  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+#  ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+#  (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+#  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+#
+# *****************************************************************************
+import os
+from scipy.io.wavfile import write
+import torch
+from mel2samp import files_to_list, MAX_WAV_VALUE
+from denoiser import Denoiser
+
+
+def main(mel_files, waveglow_path, sigma, output_dir, sampling_rate, is_fp16,
+         denoiser_strength):
+    mel_files = files_to_list(mel_files)
+    waveglow = torch.load(waveglow_path)['model']
+    waveglow = waveglow.remove_weightnorm(waveglow)
+    waveglow.cuda().eval()
+    if is_fp16:
+        from apex import amp
+        waveglow, _ = amp.initialize(waveglow, [], opt_level="O3")
+
+    if denoiser_strength > 0:
+        denoiser = Denoiser(waveglow).cuda()
+
+    for i, file_path in enumerate(mel_files):
+        file_name = os.path.splitext(os.path.basename(file_path))[0]
+        mel = torch.load(file_path)
+        mel = torch.autograd.Variable(mel.cuda())
+        mel = torch.unsqueeze(mel, 0)
+        mel = mel.half() if is_fp16 else mel
+        with torch.no_grad():
+            audio = waveglow.infer(mel, sigma=sigma)
+            if denoiser_strength > 0:
+                audio = denoiser(audio, denoiser_strength)
+            audio = audio * MAX_WAV_VALUE
+        audio = audio.squeeze()
+        audio = audio.cpu().numpy()
+        audio = audio.astype('int16')
+        audio_path = os.path.join(
+            output_dir, "{}_synthesis.wav".format(file_name))
+        write(audio_path, sampling_rate, audio)
+        print(audio_path)
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-f', "--filelist_path", required=True)
+    parser.add_argument('-w', '--waveglow_path',
+                        help='Path to waveglow decoder checkpoint with model')
+    parser.add_argument('-o', "--output_dir", required=True)
+    parser.add_argument("-s", "--sigma", default=1.0, type=float)
+    parser.add_argument("--sampling_rate", default=22050, type=int)
+    parser.add_argument("--is_fp16", action="store_true")
+    parser.add_argument("-d", "--denoiser_strength", default=0.0, type=float,
+                        help='Removes model bias. Start with 0.1 and adjust')
+
+    args = parser.parse_args()
+
+    main(args.filelist_path, args.waveglow_path, args.sigma, args.output_dir,
+         args.sampling_rate, args.is_fp16, args.denoiser_strength)