* add stub for nd impl

* refactored indices compute

* refactored divide step

* remove unused variables, add doc

* fix lint

* add relay op def

* add python registration

* refactor topi test

* update relay tests, but test result is weird

* workaround for weird bug

* add relay adaptive pool 3d test

* add topi tests

* update doc for 3d

* typo fix

* fix lint

* add more tests including NDHWC

No changes seem to be needed to _fused_batch_norm. It just works.

* [TESTS] Triage the testcases to fit the naming convention of the new namespaces

* Remove multiple usage of system lib to avoid test problems

This PR introduces tir::PrimFunc which will be used as the TIR function
container in the unified IR.

Also streamlined the function attributes a bit further.
- All common attributes are under tvm::attr
- TIR specific attributes are under tvm::tir::attr and comes with a tir prefix
- Use stl_style for attributes for now

* use qnn add/mul/concatenate

* remove logging

* rebased

* fix lint

* consider layout_transform in has_multiple_inputs

* refactor code

* remove debug info

* remove subclass assignment

* refactoring a little bit

* remove default value

* remove trailing whitespace

* modify test for has_multiple_inputs

Co-authored-by: Ubuntu <ubuntu@ip-172-31-40-194.us-west-2.compute.internal>

- Use fuzzy comparison for double.
- Removed the hack for BatchNormAttrs and DictAttr.

Also removed a warning from text printer printing.

The ubuntu_install_llvm.sh script started failing because of a http to
https redirect.  This patch adds the package that allows apt to handle
https transport.

Change-Id: I70bcba32a9fc75d02c54f4f21f288b2f46226689

* init

* fix template

* tweak naming

* [CUDA] Op strategy changes for Int8 schedules.

* Applying Haichen's suggestions.

* Make 4D output work for task extraction.

* Make x86 work.

* Fix lint.

* Lint fixes.

* Tests, comments, out channel a multiple of 4.

* Topi test.

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

* [REFACTOR] Streamline Function Attr interface.

There has been quite a few recent changes that depends heavily on
the function attr interface. This PR streamlines that interface by introducing
two APIs that covers most of the usages.

- GetAttr which gets a typed object for a given key
  - HasNonzeroAttr is a quick helper that calls GetAttr to quickly check an attribute
- WithAttr that creates a new function object with the given attr
  - The API comes with copy on write optimization to avoid multiple copies
  - We deliberately pick the prefix With(instead of Set) to indicate this
    function does not mutate the original input.

On the python side:
- We allow read access via func.attrs (which is a DictAttr)
- func.with_attrs to create a new instance with updated attrs.

We also get rid of the small wrapper functions and make sure the API centered around
the GetAttr and HasNonzeroAttr interface.

This PR also changes the function construction to follow the new convention.

* Address review comments

* Address review comments

* Fix doxygen path

* [TFLITE][FRONTEND]Reduce_any op parsing support

* Testcase check added to run in tf version above 1.14.0 & review comments

* Review comment, checked updated to 1.15

Set split node's range to minimum of ext and split factor or split nparts, but only when PassDownDomain is called with allow_missing == false, i.e. by InferBound. Add a helper PassUpThreadBinding() to get a map telling whether an IterVar has at least one leaf IterVar deriving from it binding to a thread. Add two unit tests. (#5044)

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

* remove pass folder

* Conditions updated to cover better user scenarios

* [1] New test case added

* [2] New test case added

* [3] Proper variable name used

* [4] Review Comments handled

* [5] Review comments handled

* [6] Review comments handled

* 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

This reverts commit 585f9ce6.

This reverts commit fe74b37a.

* [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

- This patch allows CUDA backend to emit correct code for
  selects with vector conditions, which may be produced
  by floordiv op lowering etc..

- This already works for llvm BE, as llvm select instruction
  supports vector conditions.

Signed-off-by: Wei Pan <weip@nvidia.com>

* 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