* fix_circular_deps_of_sbp_py

* address reveiw

* Revert "address reveiw"

This reverts commit 004ee6f89d7cec2972c77b40dc2659bd19078e2c.

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* fix

* fix

* address review

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* support tuple of ints size, or unpacked ints size for ones and zeros op

* refine according to comments

* add annotation for size

* support 0-dim tensor shape

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* export datasets interface

* auto format by CI

* fix docs

* add fix_datasets_export

* refine

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* Use function interface

* Delete the old interface file

* Delete the old interface file

* Delete the fifth part of the interface file

* Delete comment

* add RecordBytesDecoder

* add docs for OFRecordBytesDecoder

* update

* reformat the code

* resovlved conflits

* resolve conflicts

* resolving conflicts

* format the code

* Delete randperm.py

* format

* auto format by CI

* Update test_dataset.py

* auto format by CI

* The path in doctest fixed?

* Update test_dataset.py

* auto format by CI

* refine doctest

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* support_tensor_to/to_local

* export consistent_tensor.to_local()

* refine code

* export tensor.to()...

* refine code

* refine code

* optimize code

* refine code

* refine

* back up

* add tensor.to func

* make of_format

* remove to in pyTensor

* sync gpu data

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* backup

* refine

* rebase

* check in gen py

* merge master and fix bugs

* address pr comments

* address pr comments

* auto format by CI

* remove boxing

* refine

* Fix optional

* remove to in tensor.cpp

* update

* Support symbol placement type in functional.

* add sbp and sbp list arg

* refine

* use functional

* refactor CastConsistentOpExpr

* to_consistent(flow.B) backward

* Cache op expr

* add EagerNcclOpKernelState

* refine

* refine

* refine

* refine

* refine

* refine

* minor fix

* capture OpInterpContext

* unimplemented apply

* add GetNdSbp

* add mutex

* refine

* merge EagerConsistentTensorImpl::NewWithPhyTensor and EagerConsistentTensorImpl::NewWithoutPhyTensor into EagerConsistentTensorImpl::New

* rename functiona SyncData to SyncMetaAndData

* of_format

* add to_local to pybind

* add placement_sbp_util

* minor fix

* sync shape and data when tensor_to_local

* fix rpc_token bugs

* refactor AsyncRpcCtx

* set logical_shape correctly

* simplify implementation of consistent_tensor.to_local

* initialize rpc_token with zero

* refactor grad functions of to_consistent/to_local

* reformat and address pr comment

* reformat

* refactor eager_nccl_reduce lernel

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* Use function interface

* Delete the old interface file

* Delete the old interface file

* Delet docs ctc_greedy_decoder

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* remove experimental

* add test num

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* add multi client multi machine test

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* remove copy cores

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* use discover in bash

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* add tests in test.yml and refine

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* remove multi_client test files into test dir to reuse code

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* delete distributed_run_multi_client.py and move impl in distributed_run.py

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* if -> elif

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* try three times and upload log

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* add 'mode' arg in py

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* remove --multi_client in yml

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* skip distributed test in cpu

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* use new test container

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* add host key to all machines

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* auto format by CI

* fix python version

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* fix python version

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* Multi-Runtime for multi nn.Graph

* fix import os

* Fix BUG of IsMultiClient

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* 0-dim tensor support

* test case

* add more test

* refine

* update

* update default constructor

* reconstuct

* merge master

* remove notes

* remove useless codes

* fix comments

* fix comment

* add test case

* format

* refine

* refine

* refine

* refine

* MirroredTensorMeta::MirroredTensorMeta()

* support 0-dim slice

* support 0-dim slice grad

* refine

* auto format by CI

* refine

* refine

* auto format by CI

* refine

* fix slice bug

* auto format by CI

* fix resnet50 0-im loss uasge

* fix 0-dim tensor usage in test cases

* add skip test

* auto format by CI

* fix test_dataset

* check blobdesc.shape init

* auto format by CI

* remove useless empty shape init

* fix l1loss 0-dim error

* auto format by CI

* fix argmax op test

* fix add_n op test

* auto format by CI

* fix bce loss op test

* auto format by CI

* fix squeeze op test

* fix conv2d op test

* fix xpu_shape for clip_grad_norm

* auto format by CI

* resolve confilct

* fix multi...

* add conv3d module

* add simple test case

* use conv base class to write conv3d

* still test error

* add torch style conv3d unit test

* fix format

* add assert

* unittest still error

* auto format by CI

* fix format and autotest

* remove dir

* remove useless file

* add extra expr

* auto format by CI

* fix import

* fix doc

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* Fix optional

* update

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* add batchnorm3d module

* add testing flag, add more log

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* only test cpu device

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* feat(Tensor): support 0shape tensor

* math binary broadcast support emoty tensor input

* slice support empty tensor input and output

* fix check in slice

* test(Cat): add 0shape cat module test

* fix return type error on gcc 4.8.5

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* auto format by CI

* add module op test for empty tensor, cuda kernel support empty tensor

* format

* feat(ReduceOp): reduce op kernels support 0shape tensor

* delete files added by mistake

* refine if

* refine if

* feat(ConstantOp): constant ops support 0shape tensor

* feat(ReshapeOp): reshape kernel support 0shape tensor

* math binary and unary backward skip when elem equal to zeros

* fix(ReduceOp): fix reduce not memset bug

* support getitem output empty tensor

* fix comment

* getitem support input is empty

* reduce_like kernel support empty

* fix op test bug

* feat(ReduceOp): refine reduce ops initialize value

* format code

* fix triu bug when input is empty

* test(AbsOp): fix test bug

* test(DivOp): fix test bug

* fix clamp bug

* fix test_sub bug

* fix(ReduceOp): fix reduce op memset bug

* auto format by CI

* fix random

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* fix bug

* add cast_like functor

* convert to functional impl

* convert to functional

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* Move Global<CommNet> to env scope

* Revert Global RuntimeCtx New

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* rewrite slice_update backward

* use functional api

* fix comments

* refine

* refine

* refine

* add slice_grad functor

* refine

* auto format by CI

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* startup of dev scatter ops

* use dim scatter base class

* refine(using binop to abstract scatter update and add

* refine (use macros to implement kerenl class and functors)

* refine(description for register scatter ops/kernels)

* refine

* add inplace ops

* python wraper scatter_add inplace

* dev inplace ops

* refine dim_gather (using macros register mechanism)

* add grad of scatter_add_like

* refine (add src, like versions for scatter)

* refine src/like tensor

* gather refine(no need outplace/inplace versions)

* reformat

* refine

* test case of dim scatter

* test case for dim_scatter_add_like

* 1n2d test case for dim_scatter_add_like

* refine scatter sbp

* fail to sccater_add_like on 1n2d

* refing sbp

* refine test case, unify add and update like ops

* test case for scatter_add/update like ops finished

* test cases for scatter ops

* refine, merge test class

* startup of api docs

* add scatter api docs and assertion in python

* fix make error but still segment fault

* annotate sbp infer

* rewrite scatter kernel logic

* remove inplace proposal and fix macro name

* remove outdated atomic add

* move sbp infer

* add const and throw error

* add check

* set grad op

* add scatter scalar

* add scatter scalar gpu kernel

* add torch style backprop

* add torch style backprop check

* align with master

* remove redundant sbp check

* add test

* add float16n register

* fix sbp

* fix sbp

* add api doc

* make format

* add new line

* refine

* revert dim gather

* extract dim_scatter_add

* extracat scatter update ops

* add add/update functor

* rewrting by functors

* refine

* remove dim_gather_scatter_uitl.h

* add blank line

* refine macros for registering kerenls

* refine dim_scatter_scalar files name

* refine

* refine register ops

* refine

* add F.dim_scatter_scalar

* add scatter op

* refine docstr

* add scatter reduce arg

* finally(!): a draft for scatter constitent with pytroch

* change import package name

* remmove lazy test and add scatter_add and scatter_mul

* startup of scatter backward op

* add backward for scatter

* scatter ops backward finished

* add scatter, scatter_add test cases

* remove useless scatter_update_like

* reformat

* refine test cases

* refine according to comments

* revert op_exprt_helper

* fixed index element

* fix scatter update like expr for dim gather backward

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* rebase

* check in gen py

* merge master and fix bugs

* address pr comments

* address pr comments

* auto format by CI

* rebase

* address pr comments

* auto format by CI

* functional python_arg

* reuse ctrl rpc token for avoiding long time timeout waiting.

* fix compiler complaints

* auto format by CI

* auto format by CI

* remove unused files

* fix return type error on gcc 4.8.5

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* auto format by CI

* fix return type error in xrt

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* fix tick ibn sbp signature

* auto format by CI

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* add autotest tan tanh floor arctanh

* add autotest tan floor tan

* Add autotest  for log1p

* Code format

* delete no use import

* add eye op alignment

* amend pytorch test

* delete merge error branch

* Delete log1p.py

delete merge error branch

* amend code because the list of master change

* amend eye test code

* amend eye docsting

* amend eye docsting

* amend eye docstring

* autotest test_eye

* auto format by CI

* amend param of eye

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* add minimum and maximum

* add testcase

* fix docs

* move to python

* add elementwise min max grad func

* add autotest

* add broadcast min max grad func

* add broadcast min max testcase

* add broadcast_binary related functional

* convert gradient func to functional

* delete elementwise op_expr

* delete grad_op

* bind python

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* align view input style with torch

* fix bug

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* restruct activation grad functional

* remove old gradient func

* process prelu grad op

* auto format by CI

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* rewrite arange

* rewrite argwhere

* argwhere tensor testcase

* rewrite argmax test

* fix replicationpad2d padding size check

* rewrite replicationpad2d test

* rewrite layernorm test

* rewrite instantnorm123d test

* refine params to size_t

* fix comments

* refine test case

* auto format by CI

* auto format by CI

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* add autotest for some math ops

* add autotest for some activation ops

* clean activation tests

* clean math op tests

* fix a bug

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* refein

* refein

* refein

* port more changrs

* dirty workaround in autotest

* use cpu pkg to build doc

* fix

* fix

* dirty fix
cpu0_device

* refein

* refien

* refein

* refien

* reffine

* refein

* fix

* fix dataload api

* fix

* fix

* refein

* refein

* refein

* refei

* fix

* use a different path for lenet

* fxi

* add @flow.unittest.skip_unless_1n1d() for graph tests

* fxi

* refein

* refien

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* rebase

* check in gen py

* merge master and fix bugs

* address pr comments

* address pr comments

* auto format by CI

* functional python_arg

* auto format by CI

* remove unused files

* fix return type error on gcc 4.8.5

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* auto format by CI

* fix return type error in xrt

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* fix tick ibn sbp signature

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* mv clang tidy to simple ci

* rm timeout

* refei

* refein

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* fix return type error on gcc 4.8.5

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* fix return type error in xrt

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* Use function interface

* Delete blank lines

* modefied scalar add

* elementwise add

* broadcase add

* modified  ScalarAddByTensor

* modified Addmm

* Delete the old implementation

* fix _sub errot

* auto format by CI

* modified  _inplaceable

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* fix upsample nearest bug

* fix upsample nearest bug (#5347)

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* fix upsample bilinear bug

* fix export bug

* add conv autotest

* add dead loop error raise

* add floor auto_test

* fix random tensor generator bug

* restruct math ops test

* add atan autotest

* restruct math_ops

* fix bug

* fix conv test bug

* fix commnets

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* disable eager_op consistent mode

* auto format by CI

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* add ibverbs_qp.h

* modify the qp 2021-07-14

* optimize the qp_init_attr.cap.max_send_wr
when we send  too many message which are greater then qp_init_attr.cap.max_send_wr  it may have some problem
we use the msg_pendding_list_ to store the extra messages when the message is greater than qp_init_attr.cap.max_send_wr

* optimize the qp_init_attr.cap.max_send_wr
    when we send  too many message which are greater then qp_init_attr.cap.max_send_wr  it may have some proble
    we use the msg_pendding_list_ to store the extra messages when the message is greater than qp_init_attr.cap and clear todo

* optimize the qp_init_attr.cap.max_send_wr
    when we send  too many message which are greater then qp_init_attr.cap.max_send_wr  it may have some proble
    we use the msg_pendding_list_ to store the extra messages when the message is greater than qp_init_attr.cap and clear todo  and clear extra line

* optimize the qp_init_attr.cap.max_send_wr
    when we send  too many message which are greater then qp_init_attr.cap.max_send_wr  it may have some proble
    we use the msg_pendding_list_ to store the extra messages when the message is greater than qp_init_attr.cap and clear todo  and clear extra line and license

* optimize the qp_init_attr.cap.max_send_wr
    when we send  too many message which are greater then qp_init_attr.cap.max_send_wr  it may have some proble
    we use the msg_pendding_list_ to store the extra messages when the message is greater than qp_init_attr.cap and clear todo  and clear extra line and license and todo

* optimize the qp_init_attr.cap.max_send_wr
    when we send  too many message which are greater then qp_init_attr.cap.max_send_wr  it may have some proble
    we use the msg_pendding_list_ to store the extra messages when the message is greater than qp_init_attr.cap -2021-07-15-20:00

* fix the review and pass the test

* increase the kMaxSendWr 07-19

* fix the deconstruct function 2021-07-19

* test the first pr and make it precise

* fix the format and check the logic and remove the using_pendding_list_

* 2021-07-21

* fix the code  according to the  review

* fix the

* rewrite the pr and now we test it

* optimize the IB
when send too many message whose number is bigger then qp_init_attr.cap.max_send_wr,
I use the msg_pendding_list to store the extra message and wait for some time to send these message of the msg_pendding_list

* clear the duplicate license

* use pendding_list to optimize qp_init_attr.cap.max_send_wr of IB module

* change the format of the IB

* commit the format

* add new line 2021-07-27

* add new line 2021-07-27-19:30

* add new line 2021-07-27-19:33

* what is the problem of the format

* change what

* optimize the format

* win10 changed

* runtime

* runtime change again

* optimize the format of runtime

* optimize the format of acor_message.h

* optimize the format ofcpp

* optimize the format ofcpp  again

* optimize the format ofcpp  version0.56

* remove some head file

* fix the name of some paremeter

* merge master to the lambda7 and push it

* cleat the newline of 2021-0728

* why crlf

* optimze the format

* use the make format and optimization

* make the  EnqueuePostSendReadWR/PostPenddingSendWR be private

* use the ending_send_wr_lock_ as lock

* use the pending instead of the ending

* use the pending instead of the ending and

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* add activation

* rename swish to silu

* add selu

* add four activation op

* add softsign test

* add silu mish selu softsign

* Add softsign docs

* Add functional impl

* small fix for softsign backward

* remove flow.mish test

* add silu module test

* add selu test

* fix docs

* fix softsign docs

* fix format

* fix static cast

* merge master functional api yaml

* add torch style unittest

* Remove assert and add torch unittest

* add tensor def

* remove softsign test temporary

* add return maybe ok

* migrate nn ops to single_client dir

* migrate unittest

* remove lazy unittest

* add unittest

* fix to new directory

* Remove useless docs and single client test

* add doc

* fix docs

* add docs in oneflow and tensor namespace

* add torch autotest

* fix to new autotest

* remove outdated python code

* remove useless docs

* enlarge unittest tolerance

* Add static cast for const value

* skip softsign unittest

* skip tensor softsign

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