fix: fixing the tests for ivy.Shape method

[fnhirwa]

PR Description

Hi, @vedpatwardhan and @Ishticode I walked through the ivy.Shape class and given that shape implements the Sequence like behaviour. I believe that some of the magic methods implemented for this class always raise TypeError and I decided to remove them as they are not needed for the implementation.
Removed methods

• __mod__
• __rmod__
• __rdiv__
• __div__
• __sub__
• __rsub__
• __int__
• __floordiv__

After removing these methods I refactored all unit tests of the ivy.Shape methods as most of them were failing due to wrong passing of parameters.

Related Issue

Closes #

Checklist

• Did you add a function?
• Did you add the tests?
• Did you run your tests and are your tests passing?
• Did pre-commit not fail on any check?
• Did you follow the steps we provided?

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[vedpatwardhan]

Hey @fnhirwa, thanks for creating the PR!
Actually these methods were primarily added because the methods exist in torch.Size, tf.TensorShape, etc. Could you please check if those classes have these methods? If they don't then ofc we can remove them from the ivy.Shape class 😄

[fnhirwa]

Hey @fnhirwa, thanks for creating the PR! Actually these methods were primarily added because the methods exist in torch.Size, tf.TensorShape, etc. Could you please check if those classes have these methods? If they don't then ofc we can remove them from the ivy.Shape class 😄

Yeah makes sense,
I did a quick walkthrough and found that the methods in torch.Size that are not implemented are
numel and __getnewargs__ and for the tf.TensorShape are most_specific_common_supertype, cast, __concat__, is_subtype_of, _tf_api_names_v1, experimental_from_proto, flatten, _v2_behavior, experimental_as_proto, assert_is_compatible_with, _dims, merge_with, experimental_type_proto, __nonzero__, as_proto, most_specific_compatible_shape, placeholder_value, to_tensors, from_tensors, and _tf_api_names

So I think these are the ones we can add superset behaviour for🙄

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[vedpatwardhan]

lgtm! Feel free to merge, thanks @fnhirwa 😄