I have a function that has a "for" loop that has to iterate through a generator, but, actually, it doesn’t iterate. def join_probabilities(prob_generator, importance): probabilities, count = {}, 0 print(‘Before the "for" loop’) for text_probabilities in prob_generator: print(‘In the "for" loop’) I’ve added 2 prints, but when I run the function, I see only the ..

#### Category : generator

My model takes as input 4 arrays and is trained using the standard keras fit function in the following way: model.fit([train[0],train[1],train[2],train[3]], train_labels) These 4 arrays have the same dimension and they are in fact interchangeable. The dictionary ‘train’ is loaded into RAM. To overcome heavy overfitting and improve the performance of the model, I would ..

I need to write a Python generator that produces all possible pairs of numbers in range 0..N. The pairs must be sorted by a pair’s sum. Is it possible to implement that CPU-efficiently? Sequence example: (0, 0), (0, 1), (1, 0), (0, 2), (1, 1), (2, 0), (1, 2), (2, 1), (2, 2) A poor ..

I am trying to generate a Set product of two string using generator approach than storing it in a list as follows: def recursive_generator(l_set, index = 0, value = ""): if index == len(l_set): yield(value) else: for i in l_set[index]: recursive_generator(l_set, index + 1, value + i) def main(): _input = ["ab","de"] for i in ..

I was trying to understand asyncio in python from here. This link has the following code. What I don’t understand is the asyncio.gather() function has a * in front of the generator function. res = await asyncio.gather(*(make_random(i, 10 – i – 1) for i in range(3))) I am trying to understand what it means? and ..

I have the following python code. I am trying to understand python generators. If my understanding is correct the print_list will take much more memory than print_generator. I am using memory profiler to profile the two functions below. from memory_profiler import profile my_list = [i for i in range(100000)] my_generator = (i for i in ..

I have the following python code. I am trying to understand python generators. If my understanding is correct the print_list will take much more memory than print_generator. If this is so, how do I verify this. Profile in Jetbrains Pycharm only shows the relative times of execution of the two functions not their memroy consumption. ..

the code should be straight forward but I found that it works sometimes well and sometimes not at all. when trying to print the solutions immediately it works fine but when I try to store, use , or do anything else with them, the generator simply keeps giving the same solution over and over def ..

Whether it is correct to name function generate_ in python if it is not the generator and does not make yield. I always called function generator_ if it does yild, but didn’t think about generator. looks like generating is not just creating data with generators. Example: def generate_some_data(): return { f'{i}-key’: { ‘k1′: f’some_val_{i}’, ‘k2’: ..

What am I doing wrong here. Trying to get chunks of a generator using islice, but seems to be running infinitely. from itertools import islice size = 2 def g(): for x in range(11): print("generating: ", x) yield x while True: chunk = islice(g(), size) if not chunk: break print("at chunk") for c in chunk: ..

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