Fix Frontend Failing Test: jax, numpy, torch - math.tensorflow.math.reduce_prod

[ZJay07]

PR Description

Test was failing because of small floating point rounding difference and too small/large values causing the results to be inf in some frameworks.
Fixed by adding tolerance and min max x values.

Related Issue

Close #28541
Close #28540
Close #28539

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[Ishticode]

Hi @ZJay07
Thank you very much for the PR.
Maybe we should use safety factors instead of specifying min max values

[ZJay07]

Oh, what do you mean by a safety factor, do you mind giving me an example?

[Ishticode]

safety factor ensures values are bounded based on dtype instead of just hardcoded min or max. You can see it used with test_tensorflow_reduce_std in the same file.

[ZJay07]

Updated with safety factors similar to reduce_std. Let me know if this is correct.

[Ishticode]

Thanks @ZJay07 for the fix :)