* #1 migrate dist-related type()-> dtype()

* move datatype function from pten -> fluid/framework

* change type() in imperative into convert(dtype())

* modify xx_tensor->type into xx_tensor->dtype

* change the set_type interface and the caller

* modify xx_tensor.type into xx_tensor.dtype

* fix mutable_data(place, dtype())

* change caller of mutable_data in pten and distributed

* change the caller of mutable_data in fluid/framework

* change the caller of mutable_data in imperative directory

* mutable_data: inference

* update the call of mutable_data

* transfer MakePenScalarArray MakePtenScalar ResetHolderWithType

* pass the compile. the next step is remove VarType in Pten

* fix all and remove VarType from pten. success in linux. Next task is other platform

* fix conflict with develop

* fix compiled error

* Fix reset conversion

* fix conflict

* fix compiled problem

* fix typo

* Fix << in tensor_utils.cc

* fix type->dtype

* fix unittest

* fix tensor init constructor

* fix DataTypeSize for BFloat16

* fix code style

* fix npu compiled error

* fix npu

* compile npu sucessfully

* fix conflict

* fix conflict
Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* add isclose op, test=develop

* add isclose op, test=develop

* add isclose api, test=develop

* rm useless code

* rm useless code

* update python api of isclose

* add some unittest of isclose op, test=develop

* Fix the accuracy problem of allclose op when using float64 data type in static mode.

* Format the code style.

* Still has bugs.

* Fixed allclose_op bug, which cannot deal with some cases of fp64 inputs.

* improved CUDA kernel performance.

* Changed CUDA code.

* Fixed a bug in cuda kernel which cannot deal with large dimension input, and added an unittest for it.

* Add a test case for float32 input.

* Add allclose Op, and its function is analogous to numpy.allclose. It returns True if two tensors are elementwise equal within a tolerance.