Looking up instance with Name=trnfft-ci-trn1 in us-east-1...
Instance: i-0ae0e12e04e6d29f3
Starting instance...
Waiting for instance-running...
Waiting for SSM agent...
SSM agent online.
Sending benchmark command (SHA=6a00c2aca985b9341f75b240824b6e3e312081a6)...
Command ID: db23df21-24c3-4a84-a5d8-4272a53373c6
Waiting for benchmarks to complete (this may take 10+ minutes)...

=== Run status: Success ===
=== STDOUT (tail) ===
    ???
neuronxcc/nki/_torch_xla.py:129: in neuronxcc.nki._torch_xla.PyTorchXLAKernel.__call__
    ???
neuronxcc/nki/compiler/backends/neuron/FrameworkKernel.py:258: in neuronxcc.nki.compiler.backends.neuron.FrameworkKernel.FrameworkKernel.dump_config_with_boundargs
    ???
neuronxcc/nki/compiler/backends/neuron/TraceKernel.py:386: in neuronxcc.nki.compiler.backends.neuron.TraceKernel.TraceKernel.specialize_and_call
    ???
neuronxcc/nki/compiler/backends/neuron/TraceKernel.py:389: in neuronxcc.nki.compiler.backends.neuron.TraceKernel.TraceKernel.specialize_and_call
    ???
neuronxcc/nki/compiler/backends/neuron/TraceKernel.py:397: in neuronxcc.nki.compiler.backends.neuron.TraceKernel.TraceKernel.expand_kernel_with_ctx
    ???
neuronxcc/nki/compiler/backends/neuron/TraceKernel.py:424: in neuronxcc.nki.compiler.backends.neuron.TraceKernel.TraceKernel.expand_kernel_with_ctx
    ???
neuronxcc/nki/compiler/backends/neuron/TraceKernel.py:409: in neuronxcc.nki.compiler.backends.neuron.TraceKernel.TraceKernel.expand_kernel_with_ctx
    ???
trnfft/nki/dispatch.py:272: in _complex_mul_kernel
    ar = nl.load(a_re_2d[:, f_off:f_end])
             ^^^^^^^^^^^^^^^^^^^^^^^
E   AssertionError: slice with variable size is not supported
----------------------------- Captured stdout call -----------------------------
Neuron NKI - Kernel call: _complex_mul_kernel(a_real = Tensor(shape: (1024, 512), dtype: float32), a_imag = Tensor(shape: (1024, 512), dtype: float32), b_real = Tensor(shape: (1024, 512), dtype: float32), b_imag = Tensor(shape: (1024, 512), dtype: float32))
=============================== warnings summary ===============================
benchmarks/bench_fft.py::TestSTFT::test_stft_torch
  /opt/aws_neuronx_venv_pytorch_2_9/lib/python3.12/site-packages/torch/functional.py:681: UserWarning: A window was not provided. A rectangular window will be applied,which is known to cause spectral leakage. Other windows such as torch.hann_window or torch.hamming_window are recommended to reduce spectral leakage.To suppress this warning and use a rectangular window, explicitly set `window=torch.ones(n_fft, device=<device>)`. (Triggered internally at /pytorch/aten/src/ATen/native/SpectralOps.cpp:836.)
    return _VF.stft(  # type: ignore[attr-defined]

benchmarks/bench_fft.py::TestComplexMask::test_mask_nki[mask_shape2]
  benchmarks/bench_fft.py:345: PytestBenchmarkWarning: Benchmark fixture was not used at all in this test!
    @pytest.mark.neuron

../../../opt/aws_neuronx_venv_pytorch_2_9/lib/python3.12/site-packages/_pytest/cacheprovider.py:475
  /opt/aws_neuronx_venv_pytorch_2_9/lib/python3.12/site-packages/_pytest/cacheprovider.py:475: PytestCacheWarning: cache could not write path /home/ubuntu/trnfft/.pytest_cache/v/cache/nodeids: [Errno 13] Permission denied: '/home/ubuntu/trnfft/.pytest_cache/v/cache/nodeids'
    config.cache.set("cache/nodeids", sorted(self.cached_nodeids))

../../../opt/aws_neuronx_venv_pytorch_2_9/lib/python3.12/site-packages/_pytest/cacheprovider.py:429
  /opt/aws_neuronx_venv_pytorch_2_9/lib/python3.12/site-packages/_pytest/cacheprovider.py:429: PytestCacheWarning: cache could not write path /home/ubuntu/trnfft/.pytest_cache/v/cache/lastfailed: [Errno 13] Permission denied: '/home/ubuntu/trnfft/.pytest_cache/v/cache/lastfailed'
    config.cache.set("cache/lastfailed", self.lastfailed)

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

----------------------------------------------------------------------------------------------------------------------- benchmark: 69 tests -----------------------------------------------------------------------------------------------------------------------
Name (time in us)                                               Min                        Max                       Mean                  StdDev                     Median                     IQR            Outliers          OPS            Rounds  Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_fft_torch[256]                                          8.7780 (1.0)              29.7400 (1.0)              13.1522 (1.0)            9.2787 (6.10)              8.8680 (1.0)            5.8202 (49.96)         1;1  76,032.9069 (1.0)           5           1
test_bluestein_torch[127]                                   13.9340 (1.59)             46.9120 (1.58)             21.0226 (1.60)          14.4938 (9.54)             14.3970 (1.62)           9.6485 (82.82)         1;1  47,567.8555 (0.63)          5           1
test_mask_trnfft_pytorch[mask_shape0]                       14.3620 (1.64)             63.5630 (2.14)             14.9007 (1.13)           1.5201 (1.0)              14.7040 (1.66)           0.1830 (1.57)      352;406  67,110.9870 (0.88)      19333           1
test_fftn_torch[fftn_shape0]                                16.6600 (1.90)            103.6460 (3.49)             35.3242 (2.69)          38.2326 (25.15)            18.3700 (2.07)          24.8387 (213.21)        1;1  28,309.2045 (0.37)          5           1
test_fft2_torch[fft2_shape0]                                18.8180 (2.14)             41.8530 (1.41)             20.3268 (1.55)           3.4066 (2.24)             19.5535 (2.20)           0.3710 (3.18)         9;17  49,196.1138 (0.65)        204           1
test_fft_torch[1024]                                        26.5830 (3.03)             40.2650 (1.35)             29.1389 (2.22)           4.5048 (2.96)             27.5340 (3.10)           0.1165 (1.0)           2;3  34,318.4246 (0.45)         15           1
test_batched_fft_torch[batched_shape0]                      40.2410 (4.58)             79.0740 (2.66)             47.7532 (3.63)           3.0636 (2.02)             47.0460 (5.31)           0.2457 (2.11)      375;630  20,941.0021 (0.28)       6919           1
test_gemm_torch_complex64[128]                              43.1460 (4.92)             64.6140 (2.17)             45.6903 (3.47)           5.4693 (3.60)             44.2925 (4.99)           0.3430 (2.94)          1;3  21,886.4904 (0.29)         14           1
test_mask_trnfft_pytorch[mask_shape1]                       46.4440 (5.29)            162.3510 (5.46)             48.5634 (3.69)           4.6656 (3.07)             47.4070 (5.35)           0.6060 (5.20)      240;305  20,591.6187 (0.27)       3128           1
test_stft_torch                                             48.2010 (5.49)             89.3650 (3.00)             49.7158 (3.78)           4.2637 (2.80)             48.6800 (5.49)           0.3327 (2.86)        32;64  20,114.3496 (0.26)        591           1
test_bluestein_torch[997]                                   57.8330 (6.59)             86.1390 (2.90)             59.3211 (4.51)           3.8308 (2.52)             58.3300 (6.58)           0.2290 (1.97)       86;164  16,857.4017 (0.22)       1341           1
test_gemm_trnfft_pytorch[128]                               72.5190 (8.26)            120.2590 (4.04)             75.0208 (5.70)           6.6177 (4.35)             73.3635 (8.27)           0.5590 (4.80)          7;8  13,329.6424 (0.18)         86           1
test_batched_fft_torch[batched_shape1]                      76.3590 (8.70)            184.5730 (6.21)             78.9335 (6.00)           4.3342 (2.85)             77.7180 (8.76)           0.6540 (5.61)      542;669  12,668.8948 (0.17)       6333           1
test_fftn_torch[fftn_shape1]                                83.6240 (9.53)            130.1070 (4.37)             88.2517 (6.71)           5.4613 (3.59)             86.6880 (9.78)           1.8080 (15.52)     142;160  11,331.2278 (0.15)       1438           1
test_fft_torch[4096]                                        89.2740 (10.17)           105.1840 (3.54)             92.2393 (7.01)           5.5382 (3.64)             89.7055 (10.12)          0.9420 (8.09)          3;3  10,841.3644 (0.14)         16           1
test_fft2_torch[fft2_shape1]                                91.4410 (10.42)           123.4280 (4.15)             95.9641 (7.30)           4.4537 (2.93)             94.5320 (10.66)          1.1045 (9.48)      543;602  10,420.5632 (0.14)       5147           1
test_fft_torch[16384]                                      154.7310 (17.63)           181.5780 (6.11)            160.1539 (12.18)          5.7501 (3.78)            157.8200 (17.80)          1.7280 (14.83)       66;67   6,243.9939 (0.08)        371           1
test_linear_trnfft_pytorch[linear_shape0]                  194.8030 (22.19)           329.0350 (11.06)           203.6726 (15.49)         14.0334 (9.23)            197.3665 (22.26)          6.9400 (59.57)       48;54   4,909.8414 (0.06)        258           1
test_gemm_torch_complex64[256]                             218.0890 (24.84)           391.4030 (13.16)           296.8447 (22.57)         18.9698 (12.48)           298.1600 (33.62)         18.0580 (155.00)    401;112   3,368.7643 (0.04)       2039           1
test_gemm_trnfft_pytorch[256]                              302.3770 (34.45)           442.0550 (14.86)           320.5928 (24.38)         30.3977 (20.00)           304.8675 (34.38)         17.0975 (146.76)    217;220   3,119.2217 (0.04)       1984           1
test_bluestein_torch[4097]                                 319.9980 (36.45)           738.5670 (24.83)           329.6392 (25.06)         25.8547 (17.01)           323.0110 (36.42)         12.4935 (107.24)      30;33   3,033.6197 (0.04)       2824           1
test_mask_trnfft_pytorch[mask_shape2]                      333.8750 (38.04)           439.3650 (14.77)           344.0007 (26.16)         11.3395 (7.46)            337.1180 (38.02)         18.4970 (158.77)      144;3   2,906.9710 (0.04)        749           1
test_fft_torch[65536]                                      524.4300 (59.74)           551.3020 (18.54)           537.7740 (40.89)          8.6442 (5.69)            540.1210 (60.91)         14.6142 (125.44)        8;0   1,859.5172 (0.02)         15           1
test_fft2_torch[fft2_shape2]                               945.0470 (107.66)        1,066.5680 (35.86)           966.8814 (73.51)          8.8002 (5.79)            964.1960 (108.73)         6.8900 (59.14)       99;38   1,034.2530 (0.01)        457           1
test_mask_nki[mask_shape0]                               1,356.4130 (154.52)        3,012.9500 (101.31)        1,426.2196 (108.44)        79.2611 (52.14)         1,414.2180 (159.47)        28.1985 (242.05)      39;51     701.1543 (0.01)        601           1
test_gemm_nki[128]                                       1,463.2690 (166.70)        2,390.0440 (80.36)         1,528.2523 (116.20)        62.5903 (41.18)         1,514.9245 (170.83)        26.3600 (226.27)      51;53     654.3422 (0.01)        578           1
test_mask_nki[mask_shape1]                               1,478.9950 (168.49)        2,260.0040 (75.99)         1,576.5909 (119.87)        55.5749 (36.56)         1,568.0320 (176.82)        28.4393 (244.11)      38;33     634.2799 (0.01)        479           1
test_gemm_nki[256]                                       1,624.8120 (185.10)        2,797.2740 (94.06)         1,807.6108 (137.44)       146.7884 (96.57)         1,740.5670 (196.28)       196.7380 (>1000.0)      82;5     553.2164 (0.01)        364           1
test_gemm_torch_complex64[512]                           1,651.2980 (188.12)        2,630.3830 (88.45)         2,382.4161 (181.14)       170.7435 (112.33)        2,432.0205 (274.25)        31.0590 (266.60)      36;61     419.7420 (0.01)        490           1
test_linear_nki[linear_shape0]                           1,662.3370 (189.38)        6,578.6820 (221.21)        1,772.2007 (134.75)       227.6251 (149.75)        1,758.2740 (198.27)        76.0170 (652.51)       8;16     564.2702 (0.01)        493           1
test_gemm_trnfft_pytorch[512]                            1,822.0640 (207.57)        3,504.9570 (117.85)        2,374.2590 (180.52)       376.0312 (247.38)        2,642.3745 (297.97)       766.5455 (>1000.0)     174;0     421.1840 (0.01)        460           1
test_gemm_nki[512]                                       2,260.4460 (257.51)        7,970.2900 (268.00)        2,693.3810 (204.79)       622.2831 (409.38)        2,531.4205 (285.46)       405.4530 (>1000.0)     38;34     371.2806 (0.00)        370           1
test_linear_nki[linear_shape1]                           3,017.4430 (343.75)        6,022.6280 (202.51)        3,245.3637 (246.75)       299.5558 (197.07)        3,183.0330 (358.93)        99.1170 (850.79)      12;36     308.1319 (0.00)        262           1
test_linear_trnfft_pytorch[linear_shape1]                3,838.6050 (437.30)        4,149.6620 (139.53)        3,885.3418 (295.41)        32.1435 (21.15)         3,879.9265 (437.52)        17.7165 (152.07)      30;20     257.3776 (0.00)        232           1
test_fftn_trnfft_pytorch[fftn_shape0]                    4,086.6860 (465.56)        4,264.1390 (143.38)        4,144.6123 (315.13)        21.5911 (14.20)         4,143.2720 (467.22)        23.4113 (200.95)       56;9     241.2771 (0.00)        233           1
test_gemm_nki[1024]                                      4,488.1740 (511.30)       10,942.8350 (367.95)        5,013.3161 (381.18)       597.8650 (393.32)        4,866.6150 (548.78)       200.4500 (>1000.0)     10;23     199.4688 (0.00)        171           1
test_fft_nki[256]                                        9,590.3930 (>1000.0)      10,576.3870 (355.63)        9,773.4165 (743.10)       157.8925 (103.87)        9,739.7615 (>1000.0)      175.6795 (>1000.0)      14;3     102.3184 (0.00)         92           1
test_fft2_trnfft_pytorch[fft2_shape0]                   12,160.1740 (>1000.0)      12,329.0340 (414.56)       12,224.6685 (929.48)        26.5008 (17.43)        12,220.2320 (>1000.0)       32.2722 (277.02)       19;2      81.8018 (0.00)         81           1
test_gemm_torch_complex64[1024]                         12,485.5930 (>1000.0)      25,876.7970 (870.10)       18,074.6923 (>1000.0)    2,410.8888 (>1000.0)      18,908.5030 (>1000.0)      941.3940 (>1000.0)       6;7      55.3260 (0.00)         38           1
test_fft_nki[1024]                                      15,464.2300 (>1000.0)      16,663.0500 (560.29)       15,686.7814 (>1000.0)      204.4094 (134.48)       15,648.7520 (>1000.0)      221.8720 (>1000.0)      10;2      63.7479 (0.00)         62           1
test_gemm_trnfft_pytorch[1024]                          15,906.9160 (>1000.0)      20,649.1650 (694.32)       18,801.4504 (>1000.0)      777.5874 (511.55)       18,423.8510 (>1000.0)    1,159.4603 (>1000.0)      12;1      53.1874 (0.00)         43           1
test_fft_trnfft_pytorch[256]                            21,846.7520 (>1000.0)      22,592.4560 (759.67)       21,954.7371 (>1000.0)      120.8549 (79.51)        21,931.0790 (>1000.0)       49.3020 (423.19)        2;2      45.5483 (0.00)         36           1
test_bluestein_nki[127]                                 30,705.8710 (>1000.0)      32,559.3010 (>1000.0)      31,584.1638 (>1000.0)      487.5882 (320.77)       31,586.9670 (>1000.0)      673.9345 (>1000.0)      12;0      31.6614 (0.00)         32           1
test_fftn_trnfft_pytorch[fftn_shape1]                   31,315.1460 (>1000.0)      31,798.3400 (>1000.0)      31,542.4749 (>1000.0)      121.0013 (79.60)        31,563.7680 (>1000.0)      151.0193 (>1000.0)       8;0      31.7033 (0.00)         27           1
test_fft_nki[4096]                                      38,527.6490 (>1000.0)      41,979.3870 (>1000.0)      39,098.1557 (>1000.0)      656.5056 (431.90)       38,964.8625 (>1000.0)      454.7050 (>1000.0)       1;1      25.5767 (0.00)         26           1
test_stft_trnfft_pytorch                                48,808.9730 (>1000.0)      49,438.1280 (>1000.0)      48,986.4528 (>1000.0)      167.4873 (110.19)       48,920.9240 (>1000.0)      121.4592 (>1000.0)       4;3      20.4138 (0.00)         21           1
test_fft2_trnfft_pytorch[fft2_shape1]                   57,262.6610 (>1000.0)      57,529.7840 (>1000.0)      57,387.5912 (>1000.0)       70.6621 (46.49)        57,407.8120 (>1000.0)       96.4520 (827.91)        6;0      17.4254 (0.00)         18           1
test_bluestein_trnfft_pytorch[127]                      67,313.2890 (>1000.0)      67,663.2630 (>1000.0)      67,538.9113 (>1000.0)       93.7412 (61.67)        67,531.3160 (>1000.0)      133.8425 (>1000.0)       5;0      14.8063 (0.00)         15           1
test_bluestein_nki[997]                                 82,544.8690 (>1000.0)      86,876.3610 (>1000.0)      83,637.2191 (>1000.0)    1,098.3112 (722.55)       83,438.7840 (>1000.0)      620.6688 (>1000.0)       1;1      11.9564 (0.00)         13           1
test_fft_trnfft_pytorch[1024]                           87,820.5300 (>1000.0)      88,340.6190 (>1000.0)      88,148.3320 (>1000.0)      134.1325 (88.24)        88,181.9340 (>1000.0)      138.5685 (>1000.0)       2;1      11.3445 (0.00)         12           1
test_batched_fft_trnfft_pytorch[batched_shape0]         95,606.9000 (>1000.0)      96,663.1160 (>1000.0)      96,072.8805 (>1000.0)      342.0904 (225.05)       96,145.7280 (>1000.0)      575.3792 (>1000.0)       2;0      10.4088 (0.00)         11           1
test_batched_fft_trnfft_pytorch[batched_shape1]        105,971.8960 (>1000.0)     106,517.6180 (>1000.0)     106,306.7532 (>1000.0)      168.5399 (110.88)      106,352.6755 (>1000.0)      189.8220 (>1000.0)       3;0       9.4067 (0.00)         10           1
test_fft_nki[16384]                                    129,223.8640 (>1000.0)     132,444.4980 (>1000.0)     130,633.3754 (>1000.0)      986.4309 (648.95)      130,692.8240 (>1000.0)    1,078.7675 (>1000.0)       2;0       7.6550 (0.00)          8           1
test_fft_trnfft_pytorch[4096]                          357,823.3330 (>1000.0)     358,935.9110 (>1000.0)     358,368.2312 (>1000.0)      439.4813 (289.12)      358,264.5170 (>1000.0)      674.1123 (>1000.0)       2;0       2.7904 (0.00)          5           1
test_bluestein_nki[4097]                               434,627.2310 (>1000.0)     437,998.0570 (>1000.0)     436,805.9968 (>1000.0)    1,302.1648 (856.66)      437,314.5160 (>1000.0)    1,364.0315 (>1000.0)       1;0       2.2893 (0.00)          5           1
test_fft2_trnfft_pytorch[fft2_shape2]                  439,857.9850 (>1000.0)     445,374.5840 (>1000.0)     441,399.5536 (>1000.0)    2,267.4649 (>1000.0)     440,604.6360 (>1000.0)    2,061.5920 (>1000.0)       1;1       2.2655 (0.00)          5           1
test_batched_fft_nki[batched_shape0]                   515,410.3010 (>1000.0)     724,696.1880 (>1000.0)     562,444.1410 (>1000.0)   91,043.9317 (>1000.0)     519,479.7570 (>1000.0)   65,814.6115 (>1000.0)       1;1       1.7780 (0.00)          5           1
test_bluestein_trnfft_pytorch[997]                     543,754.1730 (>1000.0)     544,993.3840 (>1000.0)     544,298.5890 (>1000.0)      522.1696 (343.52)      544,043.4220 (>1000.0)      830.4077 (>1000.0)       2;0       1.8372 (0.00)          5           1
test_fft_nki[65536]                                    553,567.8560 (>1000.0)     572,671.7690 (>1000.0)     558,821.1986 (>1000.0)    7,940.3780 (>1000.0)     556,793.1780 (>1000.0)    7,596.6953 (>1000.0)       1;1       1.7895 (0.00)          5           1
test_stft_nki                                          758,616.9180 (>1000.0)     766,121.8750 (>1000.0)     763,351.6220 (>1000.0)    3,482.1309 (>1000.0)     765,369.7900 (>1000.0)    5,892.0355 (>1000.0)       1;0       1.3100 (0.00)          5           1
test_fft2_nki[fft2_shape0]                             885,915.0700 (>1000.0)     904,147.8280 (>1000.0)     893,434.9834 (>1000.0)    8,271.1218 (>1000.0)     888,494.0710 (>1000.0)   13,828.5870 (>1000.0)       1;0       1.1193 (0.00)          5           1
test_fft_trnfft_pytorch[16384]                       1,440,841.1720 (>1000.0)   1,442,433.8230 (>1000.0)   1,441,859.6918 (>1000.0)      651.5729 (428.65)    1,441,849.0850 (>1000.0)      904.1285 (>1000.0)       1;0       0.6935 (0.00)          5           1
test_batched_fft_nki[batched_shape1]                 2,067,473.9480 (>1000.0)   2,093,042.5490 (>1000.0)   2,078,105.6720 (>1000.0)   11,602.6400 (>1000.0)   2,073,239.8760 (>1000.0)   20,563.3020 (>1000.0)       1;0       0.4812 (0.00)          5           1
test_fftn_nki[fftn_shape0]                           2,148,695.7180 (>1000.0)   2,167,216.5130 (>1000.0)   2,155,969.8840 (>1000.0)    7,020.3822 (>1000.0)   2,153,302.5180 (>1000.0)    7,946.5945 (>1000.0)       2;0       0.4638 (0.00)          5           1
test_bluestein_trnfft_pytorch[4097]                  4,366,256.2140 (>1000.0)   4,383,097.4610 (>1000.0)   4,372,158.4084 (>1000.0)    6,585.1212 (>1000.0)   4,369,754.3990 (>1000.0)    7,515.6443 (>1000.0)       1;0       0.2287 (0.00)          5           1
test_fft2_nki[fft2_shape1]                           5,007,554.3380 (>1000.0)   5,047,638.6630 (>1000.0)   5,019,171.5348 (>1000.0)   16,454.5453 (>1000.0)   5,014,511.6240 (>1000.0)   16,866.9440 (>1000.0)       1;0       0.1992 (0.00)          5           1
test_fft_trnfft_pytorch[65536]                       5,823,493.6080 (>1000.0)   5,843,321.3620 (>1000.0)   5,833,591.5368 (>1000.0)    8,766.3747 (>1000.0)   5,829,695.7480 (>1000.0)   14,821.1965 (>1000.0)       2;0       0.1714 (0.00)          5           1
test_fft2_nki[fft2_shape2]                          32,220,894.4800 (>1000.0)  33,444,212.9910 (>1000.0)  32,622,778.2674 (>1000.0)  499,746.3264 (>1000.0)  32,441,988.8600 (>1000.0)  643,798.6942 (>1000.0)       1;0       0.0307 (0.00)          5           1
test_fftn_nki[fftn_shape1]                          51,952,079.7310 (>1000.0)  52,909,652.3720 (>1000.0)  52,381,680.6662 (>1000.0)  395,488.8551 (>1000.0)  52,258,203.1610 (>1000.0)  645,742.0030 (>1000.0)       2;0       0.0191 (0.00)          5           1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Legend:
  Outliers: 1 Standard Deviation from Mean; 1.5 IQR (InterQuartile Range) from 1st Quartile and 3rd Quartile.
  OPS: Operations Per Second, computed as 1 / Mean
=========================== short test summary info ============================
FAILED benchmarks/bench_fft.py::TestComplexMask::test_mask_nki[mask_shape2]
============ 1 failed, 69 passed, 4 warnings in 1788.49s (0:29:48) =============
BENCH_OK


Pulling results JSON via SSM (base64)...
Wrote /Users/scttfrdmn/src/trnfft/docs/benchmark_results/v0.7.0.json (   17997 bytes)

Next: scripts/bench_to_md.py /Users/scttfrdmn/src/trnfft/docs/benchmark_results/v0.7.0.json > docs/benchmarks_table.md

Stopping i-0ae0e12e04e6d29f3...
