parse model weights

convert.py

@@ -43,11 +43,8 @@
 parser.add_argument("--use-f16", type=bool, default=True)
 
 
-def parse_codec_model(checkpoint, out_dir, use_f16):
+def parse_codec_model(checkpoint, outfile, use_f16):
     """Load encodec model checkpoint."""
-    outfile = open(out_dir, "wb")
-    outfile.write(struct.pack("i", 0x67676d6c))  # ggml magic
-
     for name in checkpoint.keys():
         if "weight_g" in name:
             # the tensor has already been parsed with the corresponding "weight_v"
@@ -107,6 +104,27 @@ def parse_codec_model(checkpoint, out_dir, use_f16):
     outfile.close()
 
 
+def parse_hparams(outfile, use_f16):
+    # for now this is hardcoded as we only support the 24Khz model
+    in_channels = 1
+    hidden_dim = 128
+    n_filters = 32
+    kernel_size = 7
+    residual_kernel_size = 3
+    n_q = 32
+    n_bins = 1024
+    ftype = int(use_f16)
+
+    outfile.write(struct.pack("i", in_channels))
+    outfile.write(struct.pack("i", hidden_dim))
+    outfile.write(struct.pack("i", n_filters))
+    outfile.write(struct.pack("i", kernel_size))
+    outfile.write(struct.pack("i", residual_kernel_size))
+    outfile.write(struct.pack("i", n_q))
+    outfile.write(struct.pack("i", n_bins))
+    outfile.write(struct.pack("i", ftype))
+
+
 if __name__ == "__main__":
     args = parser.parse_args()
 
@@ -118,6 +136,15 @@ def parse_codec_model(checkpoint, out_dir, use_f16):
     outfile = Path(out_dir / "ggml-model.bin")
 
     checkpoint = torch.load(dir_model / "encodec_24khz-d7cc33bc.th", map_location="cpu")
+
+    # Step 1: insert ggml magic
+    outfile = open(out_dir, "wb")
+    outfile.write(struct.pack("i", 0x67676d6c))
+
+    # Step 2: insert hyperparameters
+    parse_hparams(outfile, args.use_f16)
+
+    # Step 3: insert weights
     parse_codec_model(checkpoint, outfile, args.use_f16)
 
     print("Done.")