Quantized Model Output vector on bright and dark image

So I trained a FaceNet model and trained it on some popularly available datasets and then did a Post Training Static Quantization per tensor. When I pass the following two bright and dark images of same person, here are the tensor vector that I get

027
015

Quantized Model Bright Image

tensor([[ 0.0561,  0.0374, -0.0187, -0.0187,  0.0187,  0.1869,  0.0000, -0.1869,
         -0.1308, -0.0935,  0.0374, -0.0374,  0.0187, -0.0187, -0.0748, -0.0935,
          0.0561,  0.1122,  0.1495,  0.0561, -0.0935, -0.0187, -0.0748, -0.0935,
         -0.0187,  0.0000,  0.0374,  0.1308,  0.0187, -0.1122,  0.1682,  0.0000,
          0.1122,  0.1308,  0.0561, -0.0374,  0.0748,  0.0748,  0.0935,  0.0187,
          0.1122, -0.0187,  0.0374, -0.0935,  0.0374,  0.0561,  0.1682,  0.0187,
          0.1308, -0.0187, -0.1308, -0.1308, -0.1682,  0.1682,  0.0000, -0.0935,
         -0.0935,  0.1682, -0.1122,  0.0000,  0.0561,  0.0000,  0.0935,  0.0561,
          0.0561,  0.0748, -0.0561,  0.0187,  0.1308,  0.0187, -0.0187,  0.0935,
         -0.0935, -0.1682,  0.0748,  0.0561,  0.0561, -0.1308,  0.1122,  0.0374,
          0.1308, -0.0374, -0.1122,  0.0000, -0.0561,  0.0935,  0.1122,  0.0000,
          0.0374,  0.0935,  0.0748, -0.0935, -0.0187,  0.0000,  0.1122,  0.0935,
          0.0935,  0.0000, -0.0561,  0.0187, -0.0748, -0.0561, -0.0374, -0.0374,
          0.0748,  0.0374,  0.1122,  0.1495,  0.0748, -0.1308, -0.0187, -0.0748,
         -0.1495,  0.1308, -0.0374,  0.0561, -0.1122, -0.1495,  0.0935,  0.0374,
          0.1122, -0.0187, -0.1682, -0.0374, -0.0374,  0.0748, -0.0374, -0.0935]])

Quantized Model Dark Image

tensor([[ 0.0000,  0.1400, -0.1400, -0.1400,  0.0000,  0.0000,  0.0000,  0.0000,
          0.0000, -0.1400,  0.1400,  0.0000, -0.1400, -0.1400, -0.1400,  0.1400,
          0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000, -0.1400,
          0.0000,  0.0000,  0.0000,  0.0000, -0.1400, -0.1400,  0.0000,  0.1400,
          0.1400,  0.0000,  0.0000,  0.1400,  0.0000,  0.0000,  0.0000,  0.0000,
          0.0000,  0.0000,  0.1400, -0.1400,  0.0000,  0.1400,  0.0000, -0.1400,
          0.1400,  0.0000,  0.0000, -0.1400,  0.0000,  0.0000,  0.0000,  0.0000,
          0.0000,  0.1400,  0.0000,  0.1400,  0.0000,  0.1400,  0.0000,  0.0000,
          0.1400,  0.0000, -0.1400,  0.0000,  0.0000, -0.1400, -0.1400,  0.1400,
          0.0000,  0.0000,  0.1400,  0.1400, -0.1400,  0.0000,  0.0000,  0.1400,
          0.0000,  0.0000, -0.1400,  0.0000,  0.0000,  0.1400,  0.1400,  0.0000,
          0.1400,  0.1400,  0.0000, -0.1400,  0.0000,  0.0000,  0.1400,  0.0000,
          0.0000,  0.0000, -0.1400,  0.0000,  0.0000,  0.0000, -0.1400, -0.1400,
          0.0000,  0.0000,  0.0000,  0.1400,  0.1400,  0.0000,  0.0000, -0.1400,
          0.0000,  0.0000,  0.0000,  0.0000, -0.1400,  0.0000,  0.0000,  0.0000,
         -0.1400,  0.1400,  0.0000,  0.0000, -0.1400,  0.0000,  0.0000,  0.1400]])

Float Model Bright Image

tensor([[ 0.0861,  0.0238,  0.0352,  0.0029,  0.0615,  0.1780, -0.0097, -0.1952,
         -0.0903, -0.0788,  0.0177, -0.0488,  0.0668,  0.0072, -0.0666, -0.1656,
          0.0768,  0.1084,  0.1639,  0.0932, -0.1083, -0.0076, -0.0793, -0.0751,
         -0.0260, -0.0168,  0.0444,  0.1023,  0.0600, -0.0857,  0.1747, -0.0428,
          0.0871,  0.1560,  0.0579, -0.0841,  0.0802,  0.1008,  0.1308,  0.0374,
          0.1278,  0.0261,  0.0285, -0.0642,  0.0745,  0.0313,  0.1240,  0.0297,
          0.0923,  0.0087, -0.1494, -0.1260, -0.1500,  0.1594,  0.0093, -0.0913,
         -0.0484,  0.1636, -0.1199, -0.0250,  0.0465, -0.0563,  0.1218,  0.0532,
          0.0462,  0.0253,  0.0085,  0.0233,  0.1121,  0.0526,  0.0266,  0.0940,
         -0.0478, -0.1638,  0.0216, -0.0090,  0.1029, -0.1500,  0.0686,  0.0167,
          0.1556, -0.0536, -0.1058, -0.0362, -0.0834,  0.0826,  0.0952, -0.0280,
          0.0196,  0.0630,  0.0713, -0.0816, -0.0254,  0.0012,  0.0710,  0.0748,
          0.0999,  0.0019, -0.0519, -0.0127, -0.0659, -0.0811, -0.0095,  0.0052,
          0.1079,  0.0399,  0.0921,  0.1234,  0.0490, -0.0954, -0.0277, -0.0552,
         -0.1533,  0.1452, -0.0379, -0.0052, -0.0722, -0.1557,  0.0774,  0.0535,
          0.1366, -0.0835, -0.1754, -0.0819, -0.0021,  0.0779,  0.0258, -0.1439]])

Float Model Dark Image

tensor([[ 0.0185,  0.0525, -0.0193,  0.0219, -0.0442,  0.1609,  0.0900, -0.1719,
         -0.1365, -0.0010,  0.0086, -0.0132,  0.0565,  0.0431, -0.1238, -0.1849,
          0.0379,  0.0340,  0.1383,  0.0240, -0.0125, -0.0194, -0.0264, -0.0702,
         -0.0551,  0.0823, -0.0586,  0.1484,  0.0281, -0.0548,  0.1889, -0.0370,
          0.1532,  0.0888,  0.1133, -0.0229, -0.0050,  0.0519,  0.1196, -0.0315,
          0.0500, -0.0685, -0.0457, -0.0130, -0.0261,  0.0653,  0.1504,  0.0326,
          0.0794, -0.0984, -0.0833, -0.1707, -0.1208,  0.1833, -0.0721, -0.0145,
         -0.1165,  0.1865, -0.0482, -0.0592, -0.0111, -0.0409,  0.0589,  0.1085,
         -0.0397,  0.1304, -0.0190,  0.0610,  0.1475,  0.0917,  0.0584,  0.0731,
         -0.1173, -0.1037,  0.1009,  0.0223,  0.0982, -0.1259,  0.0580, -0.0502,
          0.0871, -0.1097, -0.0811,  0.0649, -0.0330,  0.0082,  0.0201,  0.0177,
         -0.0395,  0.0232, -0.0185, -0.1652,  0.0592, -0.0826,  0.0182,  0.1457,
          0.0332, -0.0251,  0.0230,  0.0367, -0.0267,  0.0105, -0.0303,  0.0189,
          0.0193,  0.1108,  0.0677,  0.1400,  0.1273, -0.1494,  0.0124,  0.0039,
         -0.1346,  0.1757, -0.1120,  0.0749, -0.1457, -0.1344,  0.1237, -0.0492,
          0.1096, -0.0871, -0.1244, -0.0005,  0.0183, -0.0082, -0.0711, -0.0827]])

As can seen that the output tensor for float model and quantized model on bright image have different values in them. However the output tensor for quantized model on dark image have lots of zeros in them which doesn’t appear in the output tensor of floating model on dark image.

I would like to know why this is happening

i think it’s expected. quantized model may have accuracy drop. see the post here: Practical Quantization in PyTorch | PyTorch