gistfile1.txt

x tensor([[-0.0052,  0.0273, -0.0487, -0.0387, -0.0410]], dtype=torch.float32)
w tensor([[ -95,  -11,  -36,   60,  -30],
        [  83,  127, -109,   46,  -54],
        [-128,  -91,  -12,  101,  -98],
        [ -83,  -29,   -6, -105,   95],
        [  99,   -6,   48,   29,  -87]], dtype=torch.int8)
zero_point -2
scale 0.003393471473827958
calc w tensor([[-0.3156, -0.0305, -0.1154,  0.2104, -0.0950],
        [ 0.2884,  0.4378, -0.3631,  0.1629, -0.1765],
        [-0.4276, -0.3020, -0.0339,  0.3495, -0.3258],
        [-0.2749, -0.0916, -0.0136, -0.3495,  0.3292],
        [ 0.3427, -0.0136,  0.1697,  0.1052, -0.2884]], dtype=torch.float32)
w32 Parameter containing:
tensor([[-0.3154, -0.0306, -0.1157,  0.2098, -0.0943],
        [ 0.2889,  0.4385, -0.3616,  0.1619, -0.1773],
        [-0.4268, -0.3030, -0.0345,  0.3496, -0.3246],
        [-0.2765, -0.0932, -0.0142, -0.3502,  0.3302],
        [ 0.3415, -0.0135,  0.1684,  0.1064, -0.2871]], dtype=torch.float32)
b tensor([-0.0984,  0.1139,  0.3122,  0.0006, -0.1556], dtype=torch.float32,
       requires_grad=True)
y tensor([[-0.1012,  0.1320,  0.2986, -0.0043, -0.1544]], dtype=torch.float32)
y_ref tensor([[-9.6206e-02,  1.4302e-01,  3.0760e-01,  1.6042e-04, -1.5829e-01]],
       dtype=torch.float32)
diff tensor([[-0.0050, -0.0111, -0.0090, -0.0045,  0.0039]], dtype=torch.float32)