Missing Shapes after Cleanup transformation

[Harsh9650]

Prerequisites

Please make sure to check off these prerequisites before submitting a bug report.

• Test that the bug appears on the current version of the main branch. Make sure to include the commit hash of the commit you checked out.
• Check that the issue hasn't already been reported, by checking the currently open issues.
• If there are steps to reproduce the problem, make sure to write them down below.
• If relevant, please include the ONNX files, which were created directly before and/or after the bug.

Quick summary

cleanup transformation not fixing shape issues related the onnx graph of renet-18.

Details

Please add to the following sections to describe the bug as accurately as possible.

Steps to Reproduce

import netron
import os # netron
from IPython.display import IFrame # netron

import urllib.request
from qonnx.util.cleanup import cleanup
from qonnx.core.modelwrapper import ModelWrapper

def showInNetron(model_filename: str, localhost_url: str = None, port: int = None):
"""Shows a ONNX model file in the Jupyter Notebook using Netron.

:param model_filename: The path to the ONNX model file.
:type model_filename: str

:param localhost_url: The IP address used by the Jupyter IFrame to show the model.
 Defaults to localhost.
:type localhost_url: str, optional

:param port: The port number used by Netron and the Jupyter IFrame to show
 the ONNX model.  Defaults to 8081.
:type port: int, optional

:return: The IFrame displaying the ONNX model.
:rtype: IPython.lib.display.IFrame
"""
try:
    port = port or int(os.getenv("NETRON_PORT", default="8081"))
except ValueError:
    port = 8081
localhost_url = localhost_url or os.getenv("LOCALHOST_URL", default="localhost")
netron.start(model_filename, address=("0.0.0.0", port), browse=False)
return IFrame(src=f"http://{localhost_url}:{port}/", width="100%", height=400)

model_url = ("https://github.com/onnx/models/raw/main/validated/vision/classification/resnet/model/resnet18-v1-7.onnx?download=")
dl_file = "/tmp/resnet18-v1-7.onnx"
urllib.request.urlretrieve(model_url, dl_file)
out_file = "/tmp/resnet18-v1-7_clean.onnx"
cleanup(dl_file, out_file=out_file, override_batchsize = 1) # Batchsize for resnet18 is set to 1.
showInNetron(out_file)

Expected behavior

All tensors should have their respective shapes after cleanup.

Actual behavior

Most tensors missing shapes.

Optional

Possible fix

Transforming the model using InferShapes transformation (from qonnx.transformation.infer_shapes import InferShapes)

Additional context

Faced this problem with only the model specified above.

[maltanar]

Thanks @Harsh9650 for reporting this. I was able to reproduce the bug, which is now fixed and merged as part of #97. Note that override_batchsize is now renamed to override_inpsize and is more generic (i.e. it is also possible to set the spatial dimensions as well as the batch size, if required -- this is handy for e.g. fully convolutional neural networks).