* [refactor][relay pass] Separate analysis and transform passes into different subfolders

* remove pass folder

* Support 3d Convolution with the ONNX frontend

* add unit tests for conv3d in onnx frontend

respond to PR formatting requests

add x86 schedules to conv3d ncdhw test

fix a doc string format issue

refactor for changed upsream API

* first attempt at conv3d autotuning

add default schedule for conv3d_ncdhw

fill in autotvm integration

add a fallback for invalid schedules

fix fallback

fix reduction order to get simd working correctly

* [intrin] exp2

* [intrin] exp10

* [intrin] log2/10

* [intrins] exp10

* [test] math intrin

* [QNN] Support 4D padding.

* Empty commit.

Co-authored-by: Ubuntu <ubuntu@ip-172-31-38-96.us-west-2.compute.internal>

* [TFLITE]elu, leaky_relu, lrn, log_softmax activation functions

* removed ops present in pr 4805

* review_comments updated

* 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.

Finally implement tan as sin/cos in llvm.

* 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

This reverts commit d992468d.

This reverts commit f346c602.

This reverts commit fc7f0783.

* [FRONTEND][TENSORFLOW] support multiply outputs

* [TENSORFLOW][TEST] add tf_testing.AddShapesToGraphDef test

* update frontend test

* retrigger CI

* [Frontend][Torch] Check graph inputs match expected

* error/warn when missing/unused graph inputs

* Change to use get_graph_input_names

* 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

* 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.

* 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

* fix unordered dictionary problem for python version 3.5

* modify style

* op based external compiler annotation

* Use TVM register directly

* Small fix

* test graph

Co-authored-by: Cody Yu <comaniac0422@gmail.com>

* Sets xgboost dependency to be 0.90, preventing
   segfaults during TVM python unit tests execution

 * This is discussed in issue #4953

* tf frontend read variable op

* pylint fix

* tf frontend freezed graph pruned ops

* add inline pass

* IsInline -> IsMarkedInlined

* fix comment

* TFLite Floor_div & floor_mod parsing code

* Review comment updated

* [Relay][FastMath] Relay pass to use fast exp/tanh

* Adding required_pass to the tests.

* FastMath test changes.

* 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

* [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

* 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

* [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

* move contrib

* lint

* address comment

* address comment

* make_loss test case

* mxnet frontend make_loss support

* added comment for make_loss

* pylint fix

* Update mxnet.py

* [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.

* [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

* call graph for relay

* CallGraphEntryNode->CallGraphEntry, __getitem__->print_var

* fix typos