- 10 Mar, 2020 3 commits
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* Add support for prim::If and prim::Loop with test cases * rebase and fix tests * add some comments * simplifying, fix float cast * parse -> convert * recursivly retrive ops in get_all_op_names * use multiple return values from block correctly, simplify loop convert * choose dtype properly for zeros and ones * simplifying, replace convert_inputs with _get_relay_input_vars * fix for while loop with non input dependent init cond * add assert on loop var update * move the condition around * better testing for seg models * rebase fix, disable inception v3 in quant test as it is too slow to load with torch-1.4 + torchvision 0.5 * simplify and add more comparison op converter
masahi committed
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- 09 Mar, 2020 1 commit
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This reverts commit fc7f0783.
Animesh Jain committed
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- 08 Mar, 2020 3 commits
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Haichen Shen committed
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* [FRONTEND][TENSORFLOW] support multiply outputs * [TENSORFLOW][TEST] add tf_testing.AddShapesToGraphDef test * update frontend test * retrigger CI
zhengdi committed -
lfengad committed
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- 07 Mar, 2020 3 commits
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Thomas Viehmann committed
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* [Frontend][Torch] Check graph inputs match expected * error/warn when missing/unused graph inputs * Change to use get_graph_input_names
Jeremy Johnson committed -
* fix unordered dictionary problem for python version 3.5 * modify style * default value of stride in torch.nn.functional.avg_pool is None * delete prev modifications * add testcase for nn.functional.avg_pool2d
pyjhzwh committed
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- 06 Mar, 2020 1 commit
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* Add relay operation relay.op.tan. * Update tan implementation in TVM. * Update tests. * Add shape function for tan. * Add missing main test to python/frontend/tensorflow/test_forward. * Revert, back to sin/cos. * Revert "Revert, back to sin/cos." This reverts commit 4da5b503b921585ba9d80944b29136142b575c40. * Fix implementation of tan in cuda. Do not support tan for float16. Simplify topi/tests/python/test_topi_math. Add testing for tan with float32 and float64. Try again to implement tan as sin/cos in llvm.
Yao Wang committed
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- 05 Mar, 2020 2 commits
- 04 Mar, 2020 2 commits
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* qnn support initial import * fix upsampling num input * imagenet tests added * add qunatized module tests * quantized module tests working * imagenet test working * fix lint * remove top level torch import to fix ci error * disable lint warning on outside toplevel import * revert parse -> convert change * add comments to qnn translation * address comments, add sample outputs * add more comments * refactor bias add and requantize step
Animesh Jain committed -
* fix unordered dictionary problem for python version 3.5 * modify style
pyjhzwh committed
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- 03 Mar, 2020 2 commits
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* op based external compiler annotation * Use TVM register directly * Small fix * test graph Co-authored-by: Cody Yu <comaniac0422@gmail.com>
Zhi committed -
* Sets xgboost dependency to be 0.90, preventing segfaults during TVM python unit tests execution * This is discussed in issue #4953
Leandro Nunes committed
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- 02 Mar, 2020 4 commits
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* tf frontend read variable op * pylint fix * tf frontend freezed graph pruned ops
maheshambule committed -
* add inline pass * IsInline -> IsMarkedInlined * fix comment
Zhi committed -
Ethan-Yan27 committed
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* TFLite Floor_div & floor_mod parsing code * Review comment updated
Samuel committed
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- 01 Mar, 2020 2 commits
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* [Relay][FastMath] Relay pass to use fast exp/tanh * Adding required_pass to the tests. * FastMath test changes.
Animesh Jain committed -
* add custom conversion map * add roi align test using custom convert map * refactor test * add support for upsampling op and test on segmentation models * remove redundant no_grad * add upsampling test case * make the default custom map None, instead of empty dict * updated tests, remove packaging and drop PT 1.2 support * add better support for aten::to and tests * add a note on dilation in x86
masahi committed
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- 29 Feb, 2020 1 commit
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* [Frontend][TFLite] Add parser support for l2_normalization * TF doesn't provide uint8 support * TFL does the normalization only if it's over the last axis * TFL uses only the default value for expilon * Change error message
Ina Dobreva committed
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- 28 Feb, 2020 1 commit
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* The initial import of refactored implementation, all tests passed * enable mobilenet v2 test * minor cleanup * reorg * fix lint * use input names that come with torch IR * fix typo * introduce parse_operators * fix lint * add _ prefix
masahi committed
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- 27 Feb, 2020 5 commits
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* [DOCS] Sphinx -- Introduce alias detection. Background: some of our namespaces import function from another namespace. For example tvm.te imports most of the operators from tvm.tir. Previously we manually exclude these aliases from the doc. However that means we can not link them by the alias name. This PR adds a sphinx callback plugin to detect such aliases, and create a rubric block on the button of its current docstring `Alias of the original class`. It is done in a way so that we can refer to the generated docs. We also fixed a few docs errors. * Fix most of the issues
Tianqi Chen committed -
* move contrib * lint * address comment * address comment
Cody Yu committed -
* make_loss test case * mxnet frontend make_loss support * added comment for make_loss * pylint fix * Update mxnet.py
maheshambule committed -
zhengdi committed
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* [REFACTOR][PY][API-CHANGE] Remove legacy python files. Remove legacy python files. Use the te namespace for most of the tensor expression primitives. - tvm.create_schedule -> tvm.te.create_schedule - tvm.placeholder -> tvm.te.placeholder - tvm.compute -> tvm.te.compute * Remove top-level exposures.
Tianqi Chen committed
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- 26 Feb, 2020 4 commits
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* [Frontend][TFLite] Add parser support for square operator * Add parser implementation * Add relevant tests * Note: 'square' is an unary elemwise operator but it's added separately in the parser since there is no Relay 'square' op and instead we have to use 'multiply' * Change relay operation from 'multiply' to 'power' * Remove a redundant line as requested
Ina Dobreva committed -
* call graph for relay * CallGraphEntryNode->CallGraphEntry, __getitem__->print_var * fix typos
Zhi committed -
* bump up dev version * update
Haichen Shen committed -
* Initial TEDD for publishing. * 1. Fix lint issues. 2. Print intrin.body instead of intrin.name in Schedule Tree. 3. Add examples to top level APIs' comments. 4. Top level APIs don't print Dot string by default, unless outputdotstring is True. * Fix more lint issues. * Update top level API argument names and use raw strings to avoid Python lint warnings in the tests. * Disable TEDD verification, but keep TE construction. * Stop importing tedd to avoid failure. * Separate data extraction and visualization. 1. Add API tedd.dump_json(schedule) to dump a json string for the schedule data for visualization. 2. Update tests. 3. Add a tutorial. 4. Add range information to IterVars. * Update TEDD about InferBound failure. 1. TEDD doesn't call inferbound for DFG. 2. Update tutorial about the InferBound failure. * 1. Import IPython only if SVG is requested. This is required to fix a tutorial publishing faliure. 2. Fix test about IPython availability check.
yongfeng-nv committed
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- 25 Feb, 2020 3 commits
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* Add a PyTorch to Relay parser * Add alexnet, googlenet, mnasnet, shufflenet wip * Fix lint * Remove fix for shufflenet * Lower check * Pull changes from neo-ai/tvm changes * Remove commented out section * Use infer_shape everywhere * Change back to using trace instead of path in from_pytorch * Parse state_dict to add param names * Umbrella single_op under test_forwards * Remove print and cleanup call * Check if update to test broke CI * Retrigger CI * Add back in updated tests * Try splitting up tests * First pass at flexible typing, implemented for ones * Add int32 for all ops * Remove print statements * Fix lint * Broad except * Add other tensor types * Temporarily use old tests * Retrigger CI * Lower type names * Use numpy to convert in dense op * Fix lint * Remove print * Need to cleanup but verify int32 works for add * Rough tests for different types, a lot of types are not supported on CPU * Probably doesn't build, need to save work as I have to switch branches (constantly) * Parse param type * Remove print stmt in parser * Clean up some code * Working on flaot32 for bn * Add resnet18 double type * Fix lint * Temporarily move PT tests first * Temporarily add back refactored tests to fix mem issue * Add more type test and temp remove some tests * Comment out tests, hopefully CI prints a trace * Get stack trace * Remove operator dict key, rename op_name to node_id, remove dead code * Make relay map a list * Remove some hacky string stuff * Move to PyTorch 1.4 * Remove input_type as param * Remove _get_fill_value, fix full ops * Remove unused code and combine ops for identity and none * Remove fn_param * Clean up main loop * Remove useless if/else for outputs * Remove ir_names, only used once * Remove some string hacking * Remove string parsing to get output name * Fix bug with output sizes of nodes * Use attributeNames in parse ops * Remove continue and add_op in parse_op * Do this everywhere, use assert instead of explciitly type casting * Remove unnecessary swap * Slight refactor for elemwise input parse * Use a copy of graph everywhere * Rename nid_to_node_name * Refactor parse import prereqs * Clean up input node kind check * Clean up conditionals * Clean up add_op * Cleanup type for ones and zeros op * Fix lint * Add torch install to CI * Actually use torch * Try moving import torch to only where it's needed * Import torch for CI * Use take op for select * Temporarily add ignore for jit inline pass for CI * Use CompleteTensorType, might be a PT 1.2 only thing * Use different types in elemwise op * Use float16 ones * Fix float16 test * Remove the temp docker changes * Remove temp test * Temporarily comment out original tests * Remove file * Empty cache after each test * Add some prints and lower input sizes * Try using no grad * Trying to globally set grad off * Use no grad for torchvision * Remove xfail tests * Remove VGG and AlexNet due to some issues * Combine pooling tests * Remove extra test file * Remove single op, remove larger pooling tests * Remove maxpool3 * Remove debug prints * Remove inference call and add no_grad in measure latency * Use standard string start char * Remove redundant infer_shape in slice * Convert most to checks to just expr * Remove extra paren * More refactor of isinstance * Add helper for creating typed constants * Assert instead of return when no matching type * Remove network variants * Add no_grad when forward, remove deatch, fix lint * Change isinstance to expr in transpose * Use opnotimplemented, refactor * Fix full ops, remove duplicate tests * Never use shape field unless we know the type * Remove comma, retrigger CI * Add paren, retrigger CI * Use inline if-else for flags * Throw exception instead of assert * Remove version check for CI * Check version when doing inline pass * Fix lint * Lower more input sizes * Add new line, conv2d only accepts weight as expr * Use tvm.runtime.ndarray * Remove change to torch version install * Try no grad for mobilenet * Fix lint * Fix lint again * Revert to last passing * Delete test files * Ignore lint * Revert back * Comment out mobilenet * Clean up compare compiled and baseline outputs * Use IRModule * Add todos * Refactor use_bias * Add todo for fix conv op channels * Change input to data type * Remove todo * Handle channel multiplier > 1
Alex Wong committed -
* Use opencv reisze method for preprocessing of image in darknet * Use opencv reisze method for preprocessing of image in darknet * Fix pylint issues
vizero1 committed -
GaussianDropout & GaussianNoise are active only during training time. This can be skipped during inference.
Samuel committed
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- 24 Feb, 2020 1 commit
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* relay op strategy fix lint bitpack strategy bitserial_dense (#6) * update strategy * address comments fix a few topi test Dense strategy (#5) * dense * add biforst; remove comments * address comment Refactor x86 conv2d_NCHWc (#4) * Refactor x86 conv2d * Add x86 depthwise_conv2d_NCHWc * Add back topi x86 conv2d_nchw * Merge x86 conv2d_nchw and conv2d_NCHWc * Minor fix for x86 conv2d fix more strategy Add x86 conv2d_NCHWc_int8 strategy (#8) * Add x86 conv2d_NCHWc_int8 strategy * Remove contrib_conv2d_nchwc_int8 * Fix generic conv2d_NCHWc for int8 * Fix topi arm_cpu conv2d_NCHWc_int8 update x86 conv2d enable specify relay ops to be tuned for autotvm add cuda conv2d strategy add conv2d strategy for rocm add conv2d strategy for hls add conv2d strategy for arm cpu add conv2d strategy for mali add conv2d strategy for bifrost add conv2d strategy for intel graphics clean up and fix lint remove template keys from autotvm remove 2 in the func name address comments fix * fix bugs * lint * address comments * add name to op implement * Modify topi tests (#9) * Add pooling, reorg, softmax and vision * Add lrn * fix topi test * fix more topi test * lint * address comments * x * fix more tests & bugs * Modify more tests (#10) * Modify tests for bitserial_conv2d, bitserial_dense, bitserial_conv2d_rasp and bnn * Minor fix * More minor fix * fix more test * try to update vta using strategy * fix cpptest * x * fix rebase err * Fix two tests (#11) * change autotvm log format * lint * minor fix * try fix vta test * fix rebase err * tweak * tmp hack for vta pass * fix tutorial * fix * fix more tutorials * fix vta tutorial * minor * address comments * fix * address comments * fix cpptest * fix docs * change data structure name and api * address comments * lint * fix rebase err * updates * fix winograd test * fix doc * rebase * upgrade tophub version number * fix bug * re-enable vta tsim test after tophub is upgraded * fix vta test to use the correct args so the config can be found in tophub Co-authored-by: Yao Wang <kevinthesunwy@gmail.com>
Haichen Shen committed
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- 21 Feb, 2020 1 commit
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* add TFLite version check for 'ceil' and 'cos' * fix name check of test_op for positive inputs * add error message for operator not found in the installed fbs schema
Ina Dobreva committed
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- 20 Feb, 2020 1 commit
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* Fix Python docstrings * More fixes * Fix lint
Cody Yu committed
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