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gamebook.scss

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    test.py 1.03 KiB
    import torch
    import numpy as np
    from src.data.generators import KSAT_Generator
    from src.csp.csp_data import CSP_Data
    
    # ksat_generator = KSAT_Generator(min_n=3, max_n=3, min_k=2, max_k=2, min_alpha=1.0, max_alpha=1.0)
    #
    # # Create a random Boolean satisfiability instance
    # csp_data_instance = ksat_generator.create_random_instance()
    #
    # logits = torch.ones((csp_data_instance.num_val,), device=csp_data_instance.device, dtype=torch.float32)
    # assignment, _ = csp_data_instance.hard_assign_sample(logits)
    #
    # print("Generated Assignment:", assignment)
    # is_satisfied = csp_data_instance.constraint_is_sat(assignment)
    x = torch.as_tensor([1, 0, 1, 0, 2, 2, 0, 2, 0, 1]).view(2, 5)
    a = x.view(2, 1, -1)
    b = x.view(2, -1, 1)
    print(a)
    c = a == b
    #
    c = c.prod(dim=0)
    rep = torch.tril(c, -1).max(dim=1)[0]
    u = 1 - rep
    rep[rep == 1] = -1
    print(torch.logical_or(u, rep))
    # a = torch.randint(2, size=(2,2,5))
    # print(a)
    # indices = torch.nonzero(a == 1, as_tuple=False)
    
    # Flatten the indices to a 1D tensor
    # flattened_indices = indices.view(-1)
    
    # print(indices)