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[TOPI][OP] Support Faster-RCNN Proposal OP on CPU #4297

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merged 4 commits into from
Nov 13, 2019

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FrozenGene
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Currently, our TVM only implement proposal op on CUDA. However, we should support Proposal op on CPU too.

@vinx13 @tqchen please help to review it.

@FrozenGene FrozenGene changed the title [OP] Support Faster-RCNN Proposal OP on CPU. [TOPI][OP] Support Faster-RCNN Proposal OP on CPU Nov 10, 2019
@tqchen tqchen requested a review from vinx13 November 10, 2019 18:08
idxm = tvm.indexmod
idxd = tvm.indexdiv

with ib.for_range(0, batch * height * width) as tid:
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In topi cpu, all vision ops are written with hybrid script instead of ir builder now. Should we keep things consistent?

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I tried to play Hybrid Script, but seems that we have some restriction so that I can not complete Hybrid Script replacement. For example:

@hybrid.script
def outer_product(a, b, x):
    first_shape = a.shape[0]
    first_shape //= 2
    c = output_tensor((3, 3), 'float32')
    for i in const_range(first_shape):
        c[0, 0] = x[i // 2]
    return c

a = tvm.placeholder((3, ), name='a')
b = tvm.placeholder((3, ), name='b')
x = [1, 2, 3]
c = outer_product(a, b, tvm.convert(x))

It will report ValueError: Const range should start from a const and iterate const times

We should change into

   first_shape = a.shape[0] // 2
    c = output_tensor((3, 3), 'float32')
    for i in const_range(first_shape):
        c[0, 0] = x[i // 2]
    return c

This make code strange. Do we have any good ways to solve it?

Another thing is GPU / CPU relay on some common functions like generate_anchor / reg_bbox and so on. Like in generate_anchor, we use math.floor, hybrid script doesn't support. So if I have to move the generate_anchor implementation into predict_bbox_ir, I meet one problem is floor. When I add it from tvm.intrin import floor, I meet problem TypeError: 'FloatImm' object does not support indexing, you could try this simple reproduce case:

@hybrid.script
def outer_product(a, b, x):
    first_shape = a.shape[0]
    #first_shape = first_shape // 2
    c = output_tensor((3, 3), 'float32')
    for i in const_range(first_shape):
        floor(3.1 / 2.0)
    return c

So must we use hybrid script? Seems hybrid script has some restriction. Welcome feedback to above problems, if we could solve, I will try to use hybrid script to continue.

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I met these issue too when I trying to migrate proposal CUDA op to hybrid, I think it’s okay to use ir builder for the time being

@vinx13 vinx13 merged commit 8cd5cce into apache:master Nov 13, 2019
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vinx13 commented Nov 13, 2019

Thanks @FrozenGene @kevinthesun this is merged

@junrushao
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@were Could you also look into the hybrid script issue?

zxy844288792 pushed a commit to zxy844288792/tvm that referenced this pull request Nov 15, 2019
* Support Proposal operator on CPU.

* PyLint space issue

* PyLint space issue

* Pylint singleton-comparison issue
zxy844288792 pushed a commit to zxy844288792/tvm that referenced this pull request Nov 15, 2019
* Support Proposal operator on CPU.

* PyLint space issue

* PyLint space issue

* Pylint singleton-comparison issue
kevinthesun pushed a commit to neo-ai/tvm that referenced this pull request Nov 25, 2019
* [TOPI][OP] Support Faster-RCNN Proposal OP on CPU (apache#4297)

* Support Proposal operator on CPU.

* PyLint space issue

* PyLint space issue

* Pylint singleton-comparison issue

* [QNN][Legalize] Specialize for Platforms without any fast Int8 arithmetic units. (apache#4307)

* fix error when memory_id is VTA_MEM_ID_OUT (apache#4330)

* [CI][DOCKER] Add ONNX runtime dep (apache#4314)

* [DOCKER] Add ONNX runtime dep

* Improve ci script

* [QNN] Quantize - Fixing the sequence of lowering. (apache#4316)

* [QNN] Use Int16 upcast in Fallback Conv2D. Fix test names. (apache#4329)

* [doc][fix] fix sphinx parsing for pass infra tutorial (apache#4337)

* change ci image version (apache#4313)

* [Codegen] remove fp16 function override for cuda  (apache#4331)

* add volatile override back

* [codegen] remove fp16 function override for cuda

* [CI] Set workspace to be per executor (apache#4336)

* [Build][Windows] Fix Windows build by including cctype (apache#4319)

* Fix build

* dummy change to retrigger CI

* dummy change to retrigger ci

* dummy change to retrigger ci

* Enable hipModuleGetGlobal() (apache#4321)

* [Relay][Pass] Add pass to remove unused functions in relay module (apache#4334)

* [Relay][Pass] Add pass to remove unused functions in relay module

* Add tests

* Fix lint

* Fix visit order

* Add pass argument

* Fix

* Add support for quant. mul operator in tflite frontend (apache#4283)

A test for qnn_mul has to be added when the qnn elemwise tests (apache#4282) get merged.

* Add topi.nn.fifo_buffer to TVM doc (apache#4343)

* Solve custom model of prelu (apache#4326)

* Deprecate NNVM warning msg (apache#4333)

* [Contrib] Add MKL DNN option (apache#4323)

* [Contrib] Add MKL DNN

* update

* update

* [Relay][Frontend][TF] Fix transpose when axes is not a param (apache#4327)

* [Relay][Frontend][TF] Use _infer_value_simulated when axes is not a const to Transpose

* uncomment tests

* dummy change to retrigger ci

* [RUNTIME] Add device query for AMD GcnArch (apache#4341)

* add gcnArch query

* kGcnArch query for cuda is a no-op

* [Test][Relay][Pass] Add test case for lambda lift (apache#4317)

* [Relay][Frontend][ONNX] operator support: DepthToSpace, SpaceToDepth (apache#4271)

* imp module is deprecated (apache#4275)

* [VTA] Bug fix for padded load with large inputs (apache#4293)

* bug fix for padded load with large inputs

* Update TensorLoad.scala

* Update test_vta_insn.py

* fix inconsistent tag name (apache#4134)

* [CodeGen] Add build config option disable_assert to control whether to generate assert (apache#4340)

* Bump up CUDA log version in tophub.py (apache#4347)

* Add check to ensure input file was successfully opened in NNVM deploy code demo (apache#4315)

* [COMMUNITY] Add DISCLAIMER, KEYS for ASF release (apache#4345)

* [COMMUNITY] Add DISCLAIMER, KEYS for ASF release

* Add file name spec

* [Relay][VM][Interpreter] Enable first-class constructors in VM and interpreter via eta expansion (apache#4218)

* Fix constructor pretty printing

* Make Module::HasDef name consistent with API

* Add VM constructor compilation via eta expansion

* Lint

* Fix CI

* Fix failing test

* Address comment

* Retrigger CI

* Retrigger CI

* Update dmlc_tvm_commit_id.txt
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5 participants