* [Eager]Fix full_like/clip with np.generic type as attribute

* support numpy genertic

* remove usless code

* add clip yaml

* import _test_eager_guad

* add default value to scalar

* add clip_grad default value

* fix test failed

* add relu6_ hardsigmoid_ leaky_relu_ Inplace APIs

* add softmax_with_cross_entropy_ Inplace API

* add clip_ scale_ add_ subtract_ Inplace APIs

* add wlist

* fix parameter of scale api

* add add_n_ Inplace API and remove log_ Inplace API

* fix elementwise_add_ and elementwise_sub_ broadcast problem

* elementwise inplace api give error message before run the op

* use broadcast_shape in elementwise inplace op

* add 8 inplace apis that is auto generated

* add unittest for all inplace apis

* add decorator for inplace apis in static mode

* fix windows blas fail of exp inplace api, change array_equal to allclose

* add flatten inplace api

* add flatten unittest

* fix flatten unittest

* add decorator

* fix grad.numpy in test_pylayer_op

* unsupport softmax_with_cross_entropy_

* add test_inplace_softmax_with_cross_entropy to static_mode_white_list

* delete __all__ in inplace_utils

* delete activation inplace function and add Tensor.inplace_func

* change paddle.inplace_ to Tensor.inplace_

* fix little problem

* add paddle in inplace_utils

support int32 and int64 kernel for clip operator 

* Fix clip input check

* Fix default min/max value

* Allow both max and min to be None

* Register op change

* Revert OP signature change

* Update `paddle.clamp`

rename to `paddle.clip`
add fast path for dygraph mode
remove `out`
rename `input` -> `x`
update doc sample

* Fix leftover `Variable` wording

* Indent doc with spaces

* Remove `:alias` in docs

* Update `enable_imperative` -> `disable_static`

* Remove `imperative`

also trigger CI

* Update tests for better coverage

* Rebase to fix `cosine_similarity`

* Fix `cosine_similarity` some more

* add clamp api, test=develop

* OP clip, merge_lod_tensor, convert/elementwise error message enhancement. test=develop

affine_channel, affine_grid, bilinear_interp, bilinear_tensor_product,
clip, crop, crop_tensor, cumsum, data_norm, expand, expand_as

test=develop

Currently, our tests run with 2 GPUs, the init time is absurdly long:
about 4s for each process.  Currently, we run each OP test on
different processes. This PR:

1. create cmake function py_test_modules which will generate the
Makefile that runs a list of Python unittest module in a single Python
process.

2. move all "python unittest compatible" (e.g., used the unittest
package, not just a regular python file). from fluid/tests to
fluid/tests/unittests.

3. cmake now will run all OP tests in fluid/tests/unittests in a
single process, except the time-consuming tests, they are separated
into different processes to utilize parallelism. Please make sure to
use the unittest package if you put the python test file in
fluid/tests/unittests

4. remove all exit(0) from fluid/tests/unittests/*.py, exit(0) is used
to disable unittest, we can not do it when running all tests in a
single process since it will terminate the process without running the
other tests. Instead, the test is disabled in
fluid/tests/unittests/CMakeLists.txt. FIXME is added for each disabled
item. Please disable the unittest from
fluid/tests/unittests/CMakeLists.txt, instead of adding exit(0) to the
Python file, for all Python file in fluid/tests/unittests/.

5. add an option WITH_FAST_BUNDLE_TEST. When OFF, will run the unit
tests in separate process so that they can be tested individually.

* "fix decode bug"

* "follow commnet"

* "fix error"

* "fix hook bug"

* fix based comment

* fix copyright

* fix based on comment

* add copyright hook

* add copyright hook

* refine copyright hook

* "test copyright hook"

* fix check style

* fix ci

* init commit

* change some dir name

Pass all forward op test