Add CvTONNX Config #1131
Add CvTONNX Config #1131
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The documentation is not available anymore as the PR was closed or merged. |
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Hi, thank you for the addition! Tests indeed pass, except the style one. Could you run |
| @@ -550,6 +550,11 @@ def inputs(self) -> Dict[str, Dict[int, str]]: | |||
| return {"pixel_values": {0: "batch_size", 1: "num_channels", 2: "height", 3: "width"}} | |||
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| class CvTOnnxConfig(ViTOnnxConfig): | |||
| DEFAULT_ONNX_OPSET = 13 | |||
| ATOL_FOR_VALIDATION = 1e-2 | |||
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This seems pretty high tbh, do you have any idea which op makes it fail?
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Are you talking about the tolerance or the opset version? Im not sure why lower tolerance doesn't work, but einsum causes an error for lower opset versions
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I am talking about the tolerance, we might have a hidden bug if we need 1e-2, or we might not, but just wanted to raise the potential issue here.
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Any way this can be checked?
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@fxmarty Done |
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LGTM, thank you for the addition!
@rishabbala Maybe before merging, could you try to run the export on a larger CvT model and see what the diff is versus pytorch in the validation?
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The diff for cvt-13 is 3.5e-3, for cvt-13-384-22k it is 6e-3 and for cvt-21 it is 2.7e-3. Should I reduce the tolerance? |
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Sounds fine to me, thanks! |
What does this PR do?
Added changes for CvT model
Fixes part of #555
Before submitting
@michaelbenayoun @fxmarty