[GSoC] Little help on GSoC 2023 Pre-requisite task

[Matrixmang0]

Hello world!

My name is Santhosh, and I am an undergrad junior Electrical and Electronics Engineering from India.

I would really rooting to work on OpenVINO projet, this summer. So, I am currently working on my GSOC pre-requisite task on Optimizing YOWOv2 model using OpenVINO. I am actually stuck at Converting the model to ONNX format, dealing with an error. Below is the code snippet, where I am facing the follwing error.

import os

# Define the path to the weights
weights_path = Path('model/yowo_v2_tiny_ava.pth')

# Define the path where the ONNX model will be saved
onnx_path = weights_path.with_suffix('.onnx')

# Define the width and height of the input image and the number of frames in the input video
IMAGE_WIDTH = 208
IMAGE_HEIGHT = 208
NUM_FRAMES = 16

# If an ONNX model with the same name already exists, remove it
if os.path.exists(onnx_path):
    os.remove(onnx_path)

# Create a dummy input tensor for the PyTorch model, with random values
dummy_input = torch.randn(1, 3, NUM_FRAMES, IMAGE_HEIGHT, IMAGE_WIDTH)

# Export the PyTorch model to ONNX format using the `torch.onnx.export()` function
torch.onnx.export(
    YOWO_model,           # The PyTorch model to export
    dummy_input,             # The dummy input tensor to use for tracing
    onnx_path,                  # The path to save the ONNX model
    verbose=False,       
    opset_version=12,     
    input_names=['input'],
    output_names=['output'], 
    dynamic_axes={       
    'input': {0: 'batch_size', 2: 'seq_length'},
    'output': {0: 'batch_size', 2: 'seq_length'}
    }
)

# Load the exported ONNX model 
onnx_model = onnx.load(onnx_path)

# Save the ONNX model 
onnx.save(onnx_model, onnx_path)

print(f"ONNX model exported to {onnx_path}.")

Error for the code!

File ~/Openvino-projects/openvino_notebooks/notebooks/YOWOv2-optimization/YOWOv2/models/backbone/backbone_2d/cnn_2d/yolo_free/yolo_free_fpn.py:204, in PaFPNELAN.forward(self, features)
    202 c6 = self.cv1(c5)
    203 c7 = F.interpolate(c6, scale_factor=2.0)
--> 204 c8 = torch.cat([c7, self.cv2(c4)], dim=1)
    205 c9 = self.head_elan_1(c8)
    206 ## P4 -> P3

RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 12 but got size 13 for tensor number 1 in the list.

This is just the final trace of the error, as the entire error log is real huge

Any help on this would really be appreciated!

[adrianboguszewski]

Transferred to openvinotoolkit/openvino_notebooks#917