activations.cpp testing in python w/ SWIG

[etash47]

Ran 8 tests (7 failed)
(attached is output test results)

• exponential (Input integers from -100 to 100): most tests failed due to decimal imprecision, tests with input larger than 88 failed due by returning 'inf' in swig

• hard sigmoid (Input integers from -100 to 100): most tests passed, tests with inputs -2, -1, 1, 2 failed due to decimal imprecision

• hyper tan (Input integers from -100 to 100): some tests passed, all tests with input between -19 and 19 failed due to decimal imprecision

• relu (Input integers from -100 to 100): all tests passed

• sigmoid (Input integers from -100 to 100): some tests passed, all tests with input between -10 and 36 failed due to decimal imprecision, tests with input larger than 88 failed by returning 'nan'

• softmax (Input integers from -100 to 100): most tests failed due to decimal imprecision, tests with input larger than 88 failed by returning '0'

• softplus (Input integers from -100 to 100): some tests passed, all tests with input between -10 and 33 failed due to decimal imprecision, tests with input larger than 88 failed by returning 'inf'

• softsign (Input integers from -100 to 100): most tests failed due to decimal imprecision

All test cases are attached
testing_module_errors.txt

[sarahaguasvivas]

Relative tolerance for Tensorflow is 1e-5

[sarahaguasvivas]

Refactored, debugged & tested all layers, all layer types passed at tolerance of 1e-5, softmax passes at tolerance of 1e-3