from __future__ import annotations

import gc
import inspect
import os
import time
from pathlib import Path
from typing import Dict, Optional, Set

import dill as pickle
import pytest
from inference.core.workflows.execution_engine.v1.executor.execution_data_manager.dynamic_batches_manager import \
    DynamicBatchIndex
from inference.core.workflows.execution_engine.v1.executor.execution_data_manager.step_input_assembler import (
    filter_to_valid_prefix_chains, get_masks_intersection_for_dimensions,
    intersect_masks_per_dimension)


def codeflash_wrap(codeflash_wrapped, codeflash_test_module_name, codeflash_test_class_name, codeflash_test_name, codeflash_function_name, codeflash_line_id, codeflash_loop_index, *args, **kwargs):
    test_id = f'{codeflash_test_module_name}:{codeflash_test_class_name}:{codeflash_test_name}:{codeflash_line_id}:{codeflash_loop_index}'
    if not hasattr(codeflash_wrap, 'index'):
        codeflash_wrap.index = {}
    if test_id in codeflash_wrap.index:
        codeflash_wrap.index[test_id] += 1
    else:
        codeflash_wrap.index[test_id] = 0
    codeflash_test_index = codeflash_wrap.index[test_id]
    invocation_id = f'{codeflash_line_id}_{codeflash_test_index}'
    test_stdout_tag = f"{codeflash_test_module_name}:{(codeflash_test_class_name + '.' if codeflash_test_class_name else '')}{codeflash_test_name}:{codeflash_function_name}:{codeflash_loop_index}:{invocation_id}"
    print(f'!$######{test_stdout_tag}######$!')
    exception = None
    gc.disable()
    try:
        counter = time.perf_counter_ns()
        return_value = codeflash_wrapped(*args, **kwargs)
        codeflash_duration = time.perf_counter_ns() - counter
    except Exception as e:
        codeflash_duration = time.perf_counter_ns() - counter
        exception = e
    gc.enable()
    print(f'!######{test_stdout_tag}######!')
    iteration = os.environ['CODEFLASH_TEST_ITERATION']
    with Path('{codeflash_run_tmp_dir_client_side}', f'test_return_values_{iteration}.bin').open('ab') as f:
        pickled_values = pickle.dumps((args, kwargs, exception)) if exception else pickle.dumps((args, kwargs, return_value))
        _test_name = f"{codeflash_test_module_name}:{(codeflash_test_class_name + '.' if codeflash_test_class_name else '')}{codeflash_test_name}:{codeflash_function_name}:{codeflash_line_id}".encode('ascii')
        f.write(len(_test_name).to_bytes(4, byteorder='big'))
        f.write(_test_name)
        f.write(codeflash_duration.to_bytes(8, byteorder='big'))
        f.write(len(pickled_values).to_bytes(4, byteorder='big'))
        f.write(pickled_values)
        f.write(codeflash_loop_index.to_bytes(8, byteorder='big'))
        f.write(len(invocation_id).to_bytes(4, byteorder='big'))
        f.write(invocation_id.encode('ascii'))
    if exception:
        raise exception
    return return_value

def test_empty_batch_masks():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that empty batch_masks returns None for all dimensions.'
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind([], {1, 2, 3})
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_empty_batch_masks', 'get_masks_intersection_for_dimensions', '1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_single_dimension_single_mask():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test basic case with single dimension and single mask.'
    batch_masks = [{(1,), (2,)}]
    dimensions = {1}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_single_dimension_single_mask', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_single_dimension_multiple_masks_intersection():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test intersection of multiple masks at single dimension.'
    batch_masks = [{(1,), (2,), (3,)}, {(2,), (3,), (4,)}]
    dimensions = {1}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_single_dimension_multiple_masks_intersection', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_two_dimensions_valid_chain():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with two dimensions forming a valid parent-child chain.'
    batch_masks = [{(1,), (2,), (1, 1), (1, 2), (2, 1)}, {(1,), (2,), (1, 1), (1, 2), (2, 1)}]
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_two_dimensions_valid_chain', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_three_dimensions_with_hierarchy():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with three dimensions showing hierarchical structure.'
    batch_masks = [{(1,), (2,), (1, 1), (1, 2), (2, 1), (1, 1, 1), (1, 2, 1), (2, 1, 1)}, {(1,), (2,), (1, 1), (1, 2), (2, 1), (1, 1, 1), (1, 2, 1), (2, 1, 1)}]
    dimensions = {1, 2, 3}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_three_dimensions_with_hierarchy', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_mask_with_no_common_elements_at_dimension():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test when masks have no common elements at a particular dimension.'
    batch_masks = [{(1,)}, {(2,)}]
    dimensions = {1}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_mask_with_no_common_elements_at_dimension', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_dimensions_with_missing_indices():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that masks without indices at a dimension are ignored.'
    batch_masks = [{(1,)}, {(1,), (1, 1)}]
    dimensions = {1}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_dimensions_with_missing_indices', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_empty_dimensions_set():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with empty dimensions set.'
    batch_masks = [{(1,), (2,)}]
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, set())
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_empty_dimensions_set', 'get_masks_intersection_for_dimensions', '2', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_dimensions_single_element():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with single element in dimensions.'
    batch_masks = [{(1,), (2,), (3,)}]
    dimensions = {5}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_dimensions_single_element', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_mask_empty_set():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with a mask containing an empty set.'
    batch_masks = [set()]
    dimensions = {1}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_mask_empty_set', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_multiple_empty_masks():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with multiple empty masks.'
    batch_masks = [set(), set(), set()]
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_multiple_empty_masks', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_single_mask_preserves_all_indices():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that single mask preserves all its indices.'
    batch_masks = [{(1,), (2,), (3,), (1, 1), (2, 1)}]
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_single_mask_preserves_all_indices', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_unsorted_dimensions():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that dimensions are handled correctly even if unsorted.'
    batch_masks = [{(1,), (2,)}, {(1,), (2,)}]
    dimensions = {5, 1, 3}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_unsorted_dimensions', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_large_tuple_indices():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with indices that are large tuples.'
    batch_masks = [{(1,), (1, 1), (1, 1, 1), (1, 1, 1, 1), (1, 1, 1, 1, 1)}, {(1,), (1, 1), (1, 1, 1), (1, 1, 1, 1), (1, 1, 1, 1, 1)}]
    dimensions = {1, 2, 3, 4, 5}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_large_tuple_indices', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_indices_with_various_values():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with tuple indices containing various numeric values.'
    batch_masks = [{(0,), (1,), (100,), (0, 0), (0, 1), (100, 999)}, {(0,), (1,), (100,), (0, 0), (0, 1), (100, 999)}]
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_indices_with_various_values', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_broken_hierarchy_chain():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    "Test when indices don't form complete parent-child chains."
    batch_masks = [{(1,), (2,), (1, 1), (2, 1), (2, 1, 1)}, {(1,), (2,), (1, 1), (2, 1), (2, 1, 1)}]
    dimensions = {1, 2, 3}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_broken_hierarchy_chain', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output
    if result[2]:
        pass

def test_masks_with_partial_overlap():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test masks with partial overlap at different dimensions.'
    batch_masks = [{(1,), (2,), (1, 1), (2, 1)}, {(1,), (3,), (1, 1), (1, 2)}]
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_masks_with_partial_overlap', 'get_masks_intersection_for_dimensions', '3', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_large_mask_many_indices_single_dimension():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with a large mask containing many indices at single dimension.'
    large_mask = {(i,) for i in range(1000)}
    batch_masks = [large_mask, large_mask]
    dimensions = {1}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_large_mask_many_indices_single_dimension', 'get_masks_intersection_for_dimensions', '4', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_large_mask_many_indices_multiple_dimensions():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with large mask containing many indices across multiple dimensions.'
    large_mask = set()
    for i in range(100):
        large_mask.add((i,))
    for i in range(10):
        for j in range(100):
            large_mask.add((i, j))
    batch_masks = [large_mask, large_mask]
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_large_mask_many_indices_multiple_dimensions', 'get_masks_intersection_for_dimensions', '6', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_many_masks_intersection():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test intersection of many masks.'
    base_indices_1 = {(1,), (2,), (3,), (4,), (5,)}
    base_indices_2 = {(1, 1), (1, 2), (2, 1), (3, 1), (4, 1), (5, 1)}
    combined = base_indices_1 | base_indices_2
    batch_masks = [combined for _ in range(100)]
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_many_masks_intersection', 'get_masks_intersection_for_dimensions', '6', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_deep_hierarchy_large_scale():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with deep hierarchy (many dimension levels).'
    batch_masks = [set()]
    for depth in range(1, 21):
        index = tuple([1] * depth)
        batch_masks[0].add(index)
    batch_masks.append(batch_masks[0].copy())
    dimensions = set(range(1, 21))
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_deep_hierarchy_large_scale', 'get_masks_intersection_for_dimensions', '5', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output
    for dim in dimensions:
        pass

def test_wide_hierarchy_large_scale():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with wide hierarchy (many children per parent).'
    batch_masks = [set()]
    for i in range(50):
        batch_masks[0].add((i,))
        for j in range(50):
            batch_masks[0].add((i, j))
    batch_masks.append(batch_masks[0].copy())
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_wide_hierarchy_large_scale', 'get_masks_intersection_for_dimensions', '5', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_complex_multi_mask_intersection_large():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test complex intersection with multiple large masks.'
    common_core_1 = {(i,) for i in range(0, 100, 2)}
    common_core_2 = {(i, 0) for i in range(0, 100, 2)}
    mask1 = common_core_1 | {(i,) for i in range(100, 200)} | common_core_2
    mask2 = common_core_1 | {(i,) for i in range(200, 300)} | common_core_2
    mask3 = common_core_1 | {(i,) for i in range(300, 400)} | common_core_2
    batch_masks = [mask1, mask2, mask3]
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_complex_multi_mask_intersection_large', 'get_masks_intersection_for_dimensions', '8', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_stress_test_many_dimensions():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test with many dimension levels (stress test).'
    batch_masks = [set()]
    for depth in range(1, 51):
        index = tuple(range(depth))
        batch_masks[0].add(index)
    batch_masks.append(batch_masks[0].copy())
    dimensions = set(range(1, 51))
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_stress_test_many_dimensions', 'get_masks_intersection_for_dimensions', '5', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_performance_large_indices_many_masks():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test performance with moderately large inputs.'
    base_set = set()
    for i in range(500):
        base_set.add((i,))
    batch_masks = [base_set.copy() for _ in range(50)]
    dimensions = {1}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_performance_large_indices_many_masks', 'get_masks_intersection_for_dimensions', '5', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_helper_intersect_masks_per_dimension():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test the helper function intersect_masks_per_dimension directly.'
    batch_masks = [{(1,), (2,), (1, 1), (1, 2)}, {(1,), (2,), (1, 1), (2, 2)}]
    dimensions = {1, 2}
    result = intersect_masks_per_dimension(batch_masks, dimensions)

def test_helper_filter_to_valid_prefix_chains():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test the helper function filter_to_valid_prefix_chains directly.'
    per_dim_sets = {1: {(1,), (2,)}, 2: {(1, 1), (2, 1)}}
    dimensions = {1, 2}
    result = filter_to_valid_prefix_chains(per_dim_sets, dimensions)

def test_single_large_mask_no_intersection_needed():
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that single large mask bypasses filtering logic.'
    large_mask = set()
    for i in range(500):
        large_mask.add((i,))
        for j in range(10):
            large_mask.add((i, j))
    batch_masks = [large_mask]
    dimensions = {1, 2}
    _call__bound__arguments = inspect.signature(get_masks_intersection_for_dimensions).bind(batch_masks, dimensions)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(get_masks_intersection_for_dimensions, 'tests.inference.unit_tests.test_get_masks_intersection_for_dimensions__unit_test_1', None, 'test_single_large_mask_no_intersection_needed', 'get_masks_intersection_for_dimensions', '5', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output