types-tensorflow

import tensorflow as tf def create_and_add_constants(val1: int, val2: int) -> tf.Tensor: """Creates two constant tensors from ints and adds them.""" tensor1 = tf.constant(val1, dtype=tf.int32) tensor2 = tf.constant(val2, dtype=tf.int32) return tf.add(tensor1, tensor2) def concatenate_tensors(tensors: list[tf.Tensor]) -> tf.Tensor: """Concatenates a list of tensors along axis 0.""" return tf.concat(tensors, axis=0) if __name__ == "__main__": # Example 1: Basic addition with type hints sum_result = create_and_add_constants(10, 20) print(f"Sum result (numpy value): {sum_result.numpy()}") # Example 2: Concatenation with explicit type hints tensor_a = tf.constant([1.0, 2.0], dtype=tf.float32) tensor_b = tf.constant([3.0, 4.0], dtype=tf.float32) combined_tensors = concatenate_tensors([tensor_a, tensor_b]) print(f"Concatenated tensors (numpy value): {combined_tensors.numpy()}") # To run type checking: # 1. Save this code as `tf_example.py`. # 2. Install a type checker (e.g., `pip install mypy`). # 3. Run `mypy tf_example.py` in your terminal. # Expected output: Success (no errors) if code is correctly typed.