Add test for non-integer args to batch_sample()

[mhucka]

This change adds a unit test function test_batch_sample_errors() to tensorflow_quantum/core/ops/batch_util_test.py to verify that batch_util.batch_sample correctly raises TypeError for non-integer n_samples and ValueError for n_samples <= 0.

(This change was done with the help of Jules.)

[gemini-code-assist]

Summary of Changes

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This pull request introduces new unit tests to enhance the robustness of the batch_util.batch_sample function. The added tests specifically target the validation of the n_samples argument, ensuring that appropriate errors are raised when invalid types or values are provided. This improves the overall stability and reliability of the function by preventing unexpected behavior from incorrect inputs.

Highlights

• New Unit Test Added: A new unit test function, test_batch_sample_errors(), was added to tensorflow_quantum/core/ops/batch_util_test.py.
• Error Handling Verification: The new test verifies that batch_util.batch_sample correctly raises TypeError for non-integer n_samples and ValueError for n_samples <= 0.

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Changelog

• tensorflow_quantum/core/ops/batch_util_test.py
  • Added test_batch_sample_errors to validate input arguments for batch_util.batch_sample.

Activity

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[gemini-code-assist]

Code Review

This pull request adds a unit test to ensure batch_util.batch_sample handles invalid n_samples arguments correctly by raising TypeError or ValueError. The added test cases are valid and cover non-integer types as well as non-positive integer values. I've suggested a small refactoring to the new test function to reduce code duplication and improve its maintainability.