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  1. --------------------------------------------------------------------------------
  2. Environment Summary
  3. --------------------------------------------------------------------------------
  4. PyTorch 1.4.0 compiled w/ CUDA 10.1
  5. Running with Python 3.7 and
  6.  
  7. `pip list` truncated output:
  8. numpy==1.18.1
  9. torch==1.4.0
  10. torchvision==0.5.0
  11. --------------------------------------------------------------------------------
  12. cProfile output
  13. --------------------------------------------------------------------------------
  14. 1138288 function calls (1108000 primitive calls) in 27.004 seconds
  15.  
  16. Ordered by: internal time
  17. List reduced from 6815 to 15 due to restriction <15>
  18.  
  19. ncalls tottime percall cumtime percall filename:lineno(function)
  20. 98 20.098 0.205 20.098 0.205 {method 'to' of 'torch._C._TensorBase' objects}
  21. 5 3.306 0.661 3.306 0.661 {built-in method ctc_loss}
  22. 93 1.078 0.012 1.078 0.012 {method 'cuda' of 'torch._C._TensorBase' objects}
  23. 28 0.434 0.016 0.434 0.016 {method 'uniform_' of 'torch._C._TensorBase' objects}
  24. 1545 0.333 0.000 0.333 0.000 {built-in method numpy.fft._pocketfft_internal.execute}
  25. 160 0.220 0.001 0.707 0.004 /opt/miniconda3/envs/pytorchasr/lib/python3.7/site-packages/librosa/core/spectrum.py:2461(_spectrogram)
  26. 70 0.119 0.002 0.119 0.002 {built-in method conv1d}
  27. 160 0.109 0.001 0.487 0.003 /opt/miniconda3/envs/pytorchasr/lib/python3.7/site-packages/librosa/core/spectrum.py:34(stft)
  28. 1066 0.102 0.000 0.102 0.000 {built-in method marshal.loads}
  29. 160 0.079 0.000 0.108 0.001 /opt/miniconda3/envs/pytorchasr/lib/python3.7/site-packages/librosa/filters.py:112(mel)
  30. 160 0.061 0.000 0.064 0.000 /opt/miniconda3/envs/pytorchasr/lib/python3.7/site-packages/librosa/core/spectrum.py:1507(power_to_db)
  31. 28982 0.031 0.000 0.032 0.000 {built-in method builtins.getattr}
  32. 160 0.028 0.000 0.028 0.000 {built-in method scipy.fft._pocketfft.pypocketfft.dct}
  33. 9777/3967 0.027 0.000 0.434 0.000 {built-in method numpy.core._multiarray_umath.implement_array_function}
  34. 2912/2898 0.027 0.000 0.085 0.000 {built-in method builtins.__build_class__}
  35.  
  36.  
  37. --------------------------------------------------------------------------------
  38. autograd profiler output (CPU mode)
  39. --------------------------------------------------------------------------------
  40. top 15 events sorted by cpu_time_total
  41.  
  42. ------------ --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- -----------------------------------
  43. Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg CUDA total % CUDA total CUDA time avg Number of Calls Input Shapes
  44. ------------ --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- -----------------------------------
  45. to 16.56% 5.489s 16.56% 5.489s 5.489s NaN 0.000us 0.000us 1 []
  46. to 16.29% 5.399s 16.29% 5.399s 5.399s NaN 0.000us 0.000us 1 []
  47. to 16.16% 5.355s 16.16% 5.355s 5.355s NaN 0.000us 0.000us 1 []
  48. to 15.23% 5.048s 15.23% 5.048s 5.048s NaN 0.000us 0.000us 1 []
  49. to 14.94% 4.952s 14.94% 4.952s 4.952s NaN 0.000us 0.000us 1 []
  50. ctc_loss 2.11% 698.115ms 2.11% 698.115ms 698.115ms NaN 0.000us 0.000us 1 []
  51. to 2.10% 696.654ms 2.10% 696.654ms 696.654ms NaN 0.000us 0.000us 1 []
  52. ctc_loss 2.10% 696.523ms 2.10% 696.523ms 696.523ms NaN 0.000us 0.000us 1 []
  53. ctc_loss 2.10% 695.301ms 2.10% 695.301ms 695.301ms NaN 0.000us 0.000us 1 []
  54. to 2.10% 695.000ms 2.10% 695.000ms 695.000ms NaN 0.000us 0.000us 1 []
  55. ctc_loss 2.09% 694.288ms 2.09% 694.288ms 694.288ms NaN 0.000us 0.000us 1 []
  56. to 2.09% 693.801ms 2.09% 693.801ms 693.801ms NaN 0.000us 0.000us 1 []
  57. to 2.09% 692.779ms 2.09% 692.779ms 692.779ms NaN 0.000us 0.000us 1 []
  58. ctc_loss 2.02% 668.966ms 2.02% 668.966ms 668.966ms NaN 0.000us 0.000us 1 []
  59. to 2.01% 667.492ms 2.01% 667.492ms 667.492ms NaN 0.000us 0.000us 1 []
  60. ------------ --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- -----------------------------------
  61. Self CPU time total: 33.142s
  62. CUDA time total: 0.000us
  63.  
  64. --------------------------------------------------------------------------------
  65. autograd profiler output (CUDA mode)
  66. --------------------------------------------------------------------------------
  67. top 15 events sorted by cpu_time_total
  68.  
  69. Because the autograd profiler uses the CUDA event API,
  70. the CUDA time column reports approximately max(cuda_time, cpu_time).
  71. Please ignore this output if your code does not use CUDA.
  72.  
  73. ------------ --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- -----------------------------------
  74. Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg CUDA total % CUDA total CUDA time avg Number of Calls Input Shapes
  75. ------------ --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- -----------------------------------
  76. addcmul_ 18.41% 4.543s 18.41% 4.543s 4.543s 0.03% 2.000us 2.000us 1 []
  77. addcmul_ 18.06% 4.455s 18.06% 4.455s 4.455s 0.03% 2.000us 2.000us 1 []
  78. addcmul_ 17.92% 4.423s 17.92% 4.423s 4.423s 0.05% 4.000us 4.000us 1 []
  79. addcmul_ 16.88% 4.164s 16.88% 4.164s 4.164s 0.03% 2.000us 2.000us 1 []
  80. ctc_loss 2.83% 697.706ms 2.83% 697.706ms 697.706ms 20.85% 1.577ms 1.577ms 1 []
  81. to 2.82% 696.173ms 2.82% 696.173ms 696.173ms 1.11% 84.000us 84.000us 1 []
  82. ctc_loss 2.81% 693.902ms 2.81% 693.902ms 693.902ms 21.00% 1.588ms 1.588ms 1 []
  83. ctc_loss 2.81% 693.869ms 2.81% 693.869ms 693.869ms 17.70% 1.339ms 1.339ms 1 []
  84. to 2.81% 692.557ms 2.81% 692.557ms 692.557ms 0.53% 40.000us 40.000us 1 []
  85. to 2.81% 692.366ms 2.81% 692.366ms 692.366ms 1.14% 86.000us 86.000us 1 []
  86. ctc_loss 2.73% 672.559ms 2.73% 672.559ms 672.559ms 17.27% 1.306ms 1.306ms 1 []
  87. to 2.72% 671.276ms 2.72% 671.276ms 671.276ms 0.50% 38.000us 38.000us 1 []
  88. ctc_loss 2.71% 669.494ms 2.71% 669.494ms 669.494ms 19.23% 1.454ms 1.454ms 1 []
  89. to 2.71% 668.190ms 2.71% 668.190ms 668.190ms 0.50% 38.000us 38.000us 1 []
  90. add_ 0.97% 239.802ms 0.97% 239.802ms 239.802ms 0.03% 2.000us 2.000us 1 []
  91. ------------ --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- --------------- -----------------------------------
  92. Self CPU time total: 24.673s
  93. CUDA time total: 7.561ms
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