I assume the sentence “src” have 4 words, and each word is embedding into a 16 dim vector.
code like src = torch.randn(1, 4, 16)
The first word remains unchanged, the following three words are randomly generated. you can see in the output from nn.TransformerEncoder with code encode_layer = nn.TransformerEncodeLayer(d_model=16, nhead=1, dropout=0)    transformer_encoder=nn.Transformer(encoder_layer, num_layers=1). No matter how the following words change, the embedding of the first word is the same.
I think this result is unreasonable, or is there a problem with the way I use？
>>> import torch                                                                                                                                                                                                                               │1       gcc-x64-O1  0.610533  0.617933  0.947600  0.985700
>>> import torch.nn as nn                                                                                                                                                                                                                      │2       gcc-x64-O2  0.534200  0.540700  0.918633  0.977433
>>> src = torch.randn(1,4,16)                                                                                                                                                                                                                  │3       gcc-x64-O3  0.521033  0.527467  0.911867  0.974067
>>> src                                                                                                                                                                                                                                        │4       gcc-arm-O0  0.784367  0.794967  0.982433  0.993367
tensor([[[-1.2324,  1.0855, -0.1256, -1.0511, -0.9130, -0.9795,  2.1580,                                                                                                                                                                       │5       gcc-arm-O1  0.515767  0.522133  0.925933  0.978433
           0.7377,  0.9881, -0.5899, -0.7326, -0.3581,  0.1045,  0.0146,                                                                                                                                                                       │6       gcc-arm-O2  0.455333  0.461000  0.899667  0.967267
           0.9395, -1.8705],                                                                                                                                                                                                                   │7       gcc-arm-O3  0.442933  0.448433  0.892100  0.964433
         [-0.2338, -1.1813,  0.6624,  0.4502, -0.8712,  1.5969, -0.1144,                                                                                                                                                                       │8     gcc-arm64-O0  0.880600  0.892833  0.989200  0.996600
           1.6774,  2.0996, -0.8762,  0.3418,  0.8612,  0.2751,  0.7086,                                                                                                                                                                       │9     gcc-arm64-O1  0.563933  0.570233  0.937133  0.981833
           0.1442, -0.1141],                                                                                                                                                                                                                   │10    gcc-arm64-O2  0.489733  0.495467  0.903767  0.969867
         [-1.6453,  0.3087, -0.7955, -0.4064, -0.4819,  0.0947, -1.3674,                                                                                                                                                                       │11    gcc-arm64-O3  0.476933  0.482400  0.896533  0.966433
          -1.4710,  1.5510, -0.4081,  0.4080,  1.5987,  0.6879,  1.0894,                                                                                                                                                                       │12    clang-x64-O0  0.832033  0.843267  0.979033  0.991200
           0.1054, -0.3860],                                                                                                                                                                                                                   │13    clang-x64-O1  0.551233  0.557600  0.926000  0.977367
         [ 1.4328, -0.3503, -0.8012, -0.2605, -0.2735,  0.4599, -1.1251,                                                                                                                                                                       │14    clang-x64-O2  0.537433  0.543600  0.921500  0.975667
           0.9143, -0.5636, -0.3161, -1.9138, -0.4677,  0.9299,  0.0075,                                                                                                                                                                       │15    clang-x64-O3  0.530500  0.536633  0.918333  0.974800
           0.9642,  0.6295]]])                                                                                                                                                                                                                 │16    clang-arm-O0  0.690633  0.699867  0.960400  0.983433
>>> t = src[0][0]
>>> encode_layer = nn.TransformerEncoderLayer(d_model=16, nhead=1, dropout=0)
>>> transformer_encoder = nn.TransformerEncoder(encode_layer, num_layers=1)
>>> out = transformer_encoder(src)                                                                                                                                                                                                             │20  clang-arm64-O0  0.702133  0.711600  0.953467  0.982133
>>> out                                                                                                                                                                                                                                        │21  clang-arm64-O1  0.509900  0.515867  0.913267  0.972933
tensor([[[-1.6914,  0.9598, -0.3110, -0.9993, -0.9691,  0.0186,  1.6132,                                                                                                                                                                       │22  clang-arm64-O2  0.496633  0.502500  0.909067  0.971600
           0.5669,  1.3026,  0.0505,  0.0253,  0.0407,  0.8174, -0.0248,                                                                                                                                                                       │23  clang-arm64-O3  0.492667  0.498600  0.905533  0.970800
           0.6984, -2.0979],                                                                                                                                                                                                                   │            top1   dup_top1     top100     top500
         [-1.0822, -1.7807,  0.3079,  0.3645, -0.7527,  1.7316, -0.4070,                                                                                                                                                                       │count  24.000000  24.000000  24.000000  24.000000
           1.4846,  1.6255, -1.6291,  0.2163,  0.1240, -0.0125, -0.1307,                                                                                                                                                                       │mean    0.582917   0.590207   0.929579   0.977606
           0.2133, -0.2728],                                                                                                                                                                                                                   │std     0.150039   0.152522   0.031837   0.009895
         [-1.7741,  0.4637, -0.5941, -0.5148, -0.0103, -0.2896, -1.6066,                                                                                                                                                                       │min     0.442933   0.448433   0.892100   0.964433
          -0.8462,  2.1860, -0.4621,  0.8168,  1.2694,  0.6117,  0.5622,                                                                                                                                                                       │25%     0.486533   0.492200   0.905883   0.970317
           0.6685, -0.4805],                                                                                                                                                                                                                   │50%     0.525767   0.532050   0.918483   0.975233
         [ 1.0945, -0.3281, -1.3840, -0.0261, -0.0547,  0.9100, -1.4425,                                                                                                                                                                       │75%     0.630558   0.638417   0.949067   0.982458
           1.1332, -1.0016, -0.9842, -1.8533,  0.8731,  0.8267,  0.5619,                                                                                                                                                                       │max     0.985700   1.000000   1.000000   1.000000
           0.7640,  0.9113]]], grad_fn=<NativeLayerNormBackward>)
>>> src = torch.randn(1,4,16)
>>> src[0][0] = t
>>> src
tensor([[[-1.2324,  1.0855, -0.1256, -1.0511, -0.9130, -0.9795,  2.1580,
           0.7377,  0.9881, -0.5899, -0.7326, -0.3581,  0.1045,  0.0146,
           0.9395, -1.8705],
         [-0.0318, -0.9081,  0.0209, -0.0474, -0.6776,  1.0178,  0.1818,
           0.3425, -0.3291,  0.5315, -1.1100, -0.0805, -2.8687, -0.1846,
           0.4410, -1.3325],
         [-0.3382,  0.1080, -1.1487,  0.9970, -1.3720, -0.7435, -0.6814,
          -0.3464,  1.2251,  1.0221,  0.2239, -1.7205,  0.9573, -0.1409,
          -0.2924,  0.0602],
         [-1.5206,  0.3053,  1.0292,  0.4906, -1.1222,  0.7273, -1.3435,
           0.3213, -0.6371,  1.2545,  1.5598, -0.2372,  0.0758,  0.4457,
           0.9007, -0.2775]]])
>>> out = transformer_encoder(src)
>>> out
tensor([[[-1.6914,  0.9598, -0.3110, -0.9993, -0.9691,  0.0186,  1.6132,
           0.5669,  1.3026,  0.0505,  0.0253,  0.0407,  0.8174, -0.0248,
           0.6984, -2.0979],
         [-0.1582, -0.9467,  0.6978,  0.8175, -0.8259,  2.1026, -0.3020,
           0.4182, -0.3150,  0.2300,  0.1154,  0.3126, -2.4654,  0.5631,
           0.8439, -1.0878],
         [-1.0309,  0.3078, -2.1636,  0.8545, -1.1014, -0.0249, -0.0669,
          -0.1179,  1.2710,  1.6001, -0.4917, -0.7905,  1.4325,  0.4466,
          -0.7322,  0.6074],
         [-1.8881, -0.2105,  0.9825,  0.4861, -0.8173,  0.9925, -1.7599,
           0.3325, -1.2461,  0.2011,  1.7443, -0.2333,  0.5631,  0.7407,
           0.6749, -0.5626]]], grad_fn=<NativeLayerNormBackward>)