michael/modrec-workflow
1
0
Fork 0
forked from qoherent/modrec-workflow
Code Pull Requests Workflows Activity

fixed syntax

Browse Source
This commit is contained in:
Liyu Xiao 2025-08-22 13:30:54 -04:00
parent 9f8a583857
commit 0ca66e886a
2 changed files with 3 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
scripts/application_packager/convert_to_onnx.py
View File

@ -21,7 +21,7 @@ def convert_to_onnx(ckpt_path: str, fp16: bool = False) -> None:
in_channels = 2
batch_size = 1
slice_length = int(1024 / dataset_cfg.num_slices)
slice_length = int(dataset_cfg.recording_length / dataset_cfg.num_slices)
num_classes = len(dataset_cfg.modulation_types)
model = RFClassifier(
@ -42,7 +42,7 @@ def convert_to_onnx(ckpt_path: str, fp16: bool = False) -> None:
model.eval()
# Generate random sample data
base, ext = os.path.splitext(os.path.basename(ckpt_path))
base, _ = os.path.splitext(os.path.basename(ckpt_path))
if fp16:
output_path = os.path.join("onnx_files", f"{base}.onnx")
sample_input = torch.from_numpy(

2
scripts/dataset_manager/split_dataset.py
View File

@ -90,7 +90,7 @@ def split_recording(
snippet_list = []
for data, md in recording_list:
C, N = data.shape
_, N = data.shape
L = N // num_snippets
for i in range(num_snippets):
start = i * L