Gflownet optimize loss computation

[josephdviviano]

• I've read the .github/CONTRIBUTING.md file
• My code follows the typing guidelines
• I've added appropriate tests
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Description

• Many tweaks to loss computations / score computations to enable some speedups (some significant, many are minor).
• Tried to balance typical use-cases (compile vs eager, cpu vs gpu).
• Adds vectorized ops for all losses (including flow matching).
• Added a benchmark (>1000 loc) isolating the nature of the improvement:

python tutorials/misc/bench_get_scores_all.py --device cpu --size-scale 1.0 --repeat 10
Benchmarking TB/LPV/SubTB/DB/ModDB in sequence
torch version: 2.8.0
device: cpu
dtype (TB/LPV): torch.float32
num threads: 8
size-scale: 1.0
compile: True
repeat: 10
forward-looking (DB): False

Columns: original, original+compile, current, current+compile, speedup vs original (eager and compiled).

=== TB loss ===
         N   chk    orig(ms)  orig+c(ms)    curr(ms)  curr+c(ms)     spd   spd_c
     10240  PASS     123.256     226.142     128.075     227.104    0.96    0.54
     40960  PASS     426.625     465.959     432.483     467.667    0.99    0.91
    163840  PASS    1502.938    3019.063    1511.459    3036.792    0.99    0.49

=== LPV loss ===
         N   chk    orig(ms)  orig+c(ms)    curr(ms)  curr+c(ms)     spd   spd_c
     10240  PASS     122.998     265.660     122.117     266.198    1.01    0.46
     40960  PASS     458.521     527.375     458.521     528.479    1.00    0.87
    163840  PASS    1529.146    2474.459    1535.209    2476.625    1.00    0.62

=== SubTB get_scores ===
        size   chk    orig(ms)  orig+c(ms)    curr(ms)  curr+c(ms)     spd   spd_c
80x  640  PASS   22106.916   22212.291    3425.333    5188.938    6.45    4.26
160x 1280  PASS   96741.416   98876.834   18239.584   16141.709    5.30    5.99
320x 2560  PASS  357786.179  359309.822   60888.395   57334.043    5.88    6.24

=== DB get_scores ===
   n_trans   chk    orig(ms)  orig+c(ms)    curr(ms)  curr+c(ms)     spd   spd_c
     65536  PASS    1754.916    2128.500    1561.667     943.876    1.12    1.86
    131072  PASS    2214.625    2377.625    1762.334    1003.208    1.26    2.21
    262144  PASS    2820.520    3131.541    2327.792    1145.459    1.21    2.46

=== Modified DB get_scores ===
   n_trans   chk    orig(ms)  orig+c(ms)    curr(ms)  curr+c(ms)     spd   spd_c
     65536  PASS    1986.667    2120.395    1992.729    2668.625    1.00    0.74
    131072  PASS    3331.375    3657.042    3322.604    3593.625    1.00    0.93
    262144  PASS    4761.896    4865.604    4835.500    5147.833    0.98    0.93
    ```