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The function has no problem when the input is a 3D Tensor.
However, when we enter a 4D Tensor, this function will report a bug of " wrong dimension":
Expected 3D (unbatched) or 4D (batched) input to conv2d, but got input of size: [1, 1, 3, 224, 1]
I am running a network whose input demension has to be fixed to 4.
Is there any way to enable it to input different dimensions of Tensors?
The text was updated successfully, but these errors were encountered:
---Original---
From: "Vladislav ***@***.***>
Date: Mon, Dec 12, 2022 18:53 PM
To: ***@***.***>;
Cc: "Zhang ***@***.******@***.***>;
Subject: Re: [sovrasov/flops-counter.pytorch] Is the input size of function"get_model_complexity_info()" must be fixed to 3 demensions? (Issue #102)
Hi! See #14
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You are receiving this because you authored the thread.Message ID: ***@***.***>
The function has no problem when the input is a 3D Tensor.
However, when we enter a 4D Tensor, this function will report a bug of " wrong dimension":
Expected 3D (unbatched) or 4D (batched) input to conv2d, but got input of size: [1, 1, 3, 224, 1]
I am running a network whose input demension has to be fixed to 4.
Is there any way to enable it to input different dimensions of Tensors?
The text was updated successfully, but these errors were encountered: