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[Relay] Add a PyTorch to Relay Parser #4497

Merged
merged 136 commits into from
Feb 25, 2020
Merged

[Relay] Add a PyTorch to Relay Parser #4497

merged 136 commits into from
Feb 25, 2020

Commits on Feb 24, 2020

  1. Add a PyTorch to Relay parser

    @alexwong
    alexwong committed Feb 24, 2020
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  2. Add alexnet, googlenet, mnasnet, shufflenet wip

    @alexwong
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  3. Fix lint

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  4. Remove fix for shufflenet

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  5. Lower check

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  6. Pull changes from neo-ai/tvm changes

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  7. Remove commented out section

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  8. Use infer_shape everywhere

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  9. Change back to using trace instead of path in from_pytorch

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  10. Parse state_dict to add param names

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  11. Umbrella single_op under test_forwards

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  12. Remove print and cleanup call

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  13. Check if update to test broke CI

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  14. Retrigger CI

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  15. Add back in updated tests

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  16. Try splitting up tests

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  17. First pass at flexible typing, implemented for ones

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  18. Add int32 for all ops

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  19. Remove print statements

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  20. Fix lint

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  21. Broad except

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  22. Add other tensor types

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  23. Temporarily use old tests

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  24. Retrigger CI

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  25. Lower type names

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  26. Use numpy to convert in dense op

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  27. Fix lint

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  28. Remove print

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  29. Need to cleanup but verify int32 works for add

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  30. Rough tests for different types, a lot of types are not supported on CPU

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  31. Probably doesn't build, need to save work as I have to switch branche… 

    …s (constantly)
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  32. Parse param type

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  33. Remove print stmt in parser

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  34. Clean up some code

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  35. Working on flaot32 for bn

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  36. Add resnet18 double type

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  37. Fix lint

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  38. Temporarily move PT tests first

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  39. Temporarily add back refactored tests to fix mem issue

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  40. Add more type test and temp remove some tests

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  41. Comment out tests, hopefully CI prints a trace

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  42. Get stack trace

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  43. Remove operator dict key, rename op_name to node_id, remove dead code

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  44. Make relay map a list

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  45. Remove some hacky string stuff

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  46. Move to PyTorch 1.4

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  47. Remove input_type as param

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  48. Remove _get_fill_value, fix full ops

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  49. Remove unused code and combine ops for identity and none

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  50. Remove fn_param

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  51. Clean up main loop

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  52. Remove useless if/else for outputs

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  53. Remove ir_names, only used once

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  54. Remove some string hacking

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  55. Remove string parsing to get output name

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  56. Fix bug with output sizes of nodes

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  57. Use attributeNames in parse ops

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  58. Remove continue and add_op in parse_op

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  59. Do this everywhere, use assert instead of explciitly type casting

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  60. Remove unnecessary swap

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  61. Slight refactor for elemwise input parse

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  62. Use a copy of graph everywhere

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  63. Rename nid_to_node_name

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  64. Refactor parse import prereqs

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  65. Clean up input node kind check

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  66. Clean up conditionals

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  67. Clean up add_op

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  68. Cleanup type for ones and zeros op

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  69. Fix lint

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  70. Add torch install to CI

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  71. Actually use torch

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  72. Try moving import torch to only where it's needed

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  73. Import torch for CI

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  74. Use take op for select

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  75. Temporarily add ignore for jit inline pass for CI

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  76. Use CompleteTensorType, might be a PT 1.2 only thing

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  77. Use different types in elemwise op

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  78. Use float16 ones

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  79. Fix float16 test

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  80. Remove the temp docker changes

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  81. Remove temp test

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  82. Temporarily comment out original tests

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  83. Remove file

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  84. Empty cache after each test

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  85. Add some prints and lower input sizes

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  86. Try using no grad

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  87. Trying to globally set grad off

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  88. Use no grad for torchvision

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  89. Remove xfail tests

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  90. Remove VGG and AlexNet due to some issues

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  91. Combine pooling tests

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  92. Remove extra test file

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  93. Remove single op, remove larger pooling tests

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  94. Remove maxpool3

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  95. Remove debug prints

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  96. Remove inference call and add no_grad in measure latency

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  97. Use standard string start char

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  98. Remove redundant infer_shape in slice

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  99. Convert most to checks to just expr

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  100. Remove extra paren

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  101. More refactor of isinstance

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  102. Add helper for creating typed constants

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  103. Assert instead of return when no matching type

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  104. Remove network variants

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  105. Add no_grad when forward, remove deatch, fix lint

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  106. Change isinstance to expr in transpose

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  107. Use opnotimplemented, refactor

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  108. Fix full ops, remove duplicate tests

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  109. Never use shape field unless we know the type

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  110. Remove comma, retrigger CI

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  111. Add paren, retrigger CI

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  112. Use inline if-else for flags

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  113. Throw exception instead of assert

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  114. Remove version check for CI

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  115. Check version when doing inline pass

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  116. Fix lint

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  117. Lower more input sizes

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  118. Add new line, conv2d only accepts weight as expr

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  119. Use tvm.runtime.ndarray

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  120. Remove change to torch version install

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  121. Try no grad for mobilenet

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  122. Fix lint

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    alexwong committed Feb 24, 2020
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  123. Fix lint again

    @alexwong
    alexwong committed Feb 24, 2020
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  124. Revert to last passing

    @alexwong
    alexwong committed Feb 24, 2020
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  125. Delete test files

    @alexwong
    alexwong committed Feb 24, 2020
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  126. Ignore lint

    @alexwong
    alexwong committed Feb 24, 2020
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  127. Revert back

    @alexwong
    alexwong committed Feb 24, 2020
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  128. Comment out mobilenet

    @alexwong
    alexwong committed Feb 24, 2020
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  129. Clean up compare compiled and baseline outputs

    @alexwong
    alexwong committed Feb 24, 2020
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  130. Use IRModule

    @alexwong
    alexwong committed Feb 24, 2020
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  131. Add todos

    @alexwong
    alexwong committed Feb 24, 2020
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  132. Refactor use_bias

    @alexwong
    alexwong committed Feb 24, 2020
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  133. Add todo for fix conv op channels

    @alexwong
    alexwong committed Feb 24, 2020
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  134. Change input to data type

    @alexwong
    alexwong committed Feb 24, 2020
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  135. Remove todo

    @alexwong
    alexwong committed Feb 24, 2020
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  136. Handle channel multiplier > 1

    @alexwong
    alexwong committed Feb 24, 2020
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