onnx: ONNX shape inference does not infer shapes

Bug Report

Describe the bug

onnx.shape_inference.infer_shapes does not correctly infer shape of each layer.

System information

OS Platform and Distribution: Windows 10
ONNX version: 1.7.0
Python version: 3.7.4

Reproduction instructions

Describe the code to reproduce the behavior.

model = onnx.load("models/conv_dummy.onnx")
onnx.checker.check_model(model)
inferred_model = onnx.shape_inference.infer_shapes(model)
print(inferred_model.graph.value_info)

output:

[name: "9"
type {
  tensor_type {
    elem_type: 1
  }
}
, name: "10"
type {
  tensor_type {
    elem_type: 1
  }
}
, name: "11"
type {
  tensor_type {
    elem_type: 1
  }
}
, name: "12"
type {
  tensor_type {
    elem_type: 1
  }
}
, name: "13"
type {
  tensor_type {
    elem_type: 1
  }
}
, name: "14"
type {
  tensor_type {
    elem_type: 1
  }
}
]

Model file: models.zip

Expected behavior

Expected each entry in model.graph.value_info to have tensor shape field which tells me the shape of that layer.

Notes

Model was exported from PyTorch using torch.onnx.export

About this issue

Original URL
State: closed
Created 4 years ago
Comments: 26 (15 by maintainers)

Most upvoted comments

Good workaround. Adding a line add_value_info_for_constants(model) before shape inference runs correctly.

dtch1997 on Jul 22, 2020

The shape inference problem still persists as lot of shapes are missing when trying to parse the gpt2 onnx model from https://github.com/onnx/models/blob/main/text/machine_comprehension/gpt-2/README.md . I am using onnx version 1.13.1 . Perhaps the problem is about dynamic shape inference. Can anyone suggest any way-out to tackle dynamic shape inference?

mananta on Mar 15, 2023