* remove lstm api

* remove gru_unit api

* remove lstm in all

* remove beam-search

* remove beam_search slot

* remove lstm test code

* remove fluid.layers.nn api

* update gru-unit

* revert gru_unit white list

* remove dropout

* remove layers.matmul in nets.py

* remove layers.matmul in rnn_impl/test_quantization_pass/auto_parallel_gpt_model/test_auto_parallel_completion_gpt

* remove layers.matmul in other files

* fix

* fix

* remove layers.matmul itself

* remove ref in CMakeLists.txt and tools directory

* remove matmul in fluid.layers.nn.py

* remove matmul in fluid.dygraph.rnn.py && resotre test_matmul_op.py

* replace matmul in fluid.dygraph.rnn.py && clean api_test in test_matmul_op.py

* fix error && restore empty test_auto_search_dist_matmul_op.py

* fix check in test_auto_parallel_partitioner.py

* fix test_dist_matmul && test_flags_mkldnn_ops_on_off

* fix test_fused_attention_op_xpu.py && test_matmul_op_xpu.py

* remove test_auto_search_dist_matmul_op.py

* remove layers.matmul in auto_parallel_gpt_model.py && fix doc in fluid/io.py

* fix for matmul_grad

* fix codestyle

* fix codestyle

* resolve conflicts error

* restore unit test file but not compiled it for later remove

* fix codestyle

* fix wrong unittest skip

* fix unittest delete

* fix scale cost

* fix scale cost

* resolve conflicts error

* resolve conflicts error
Co-authored-by: Njakpiase <jakpia21@gmail.com>

move paddle.fluid.layers.tensor.create_parameter to paddle.tensor.creation.create_parameter (#48579)

* clear fluid apis in fleet and passes

* fix model.py

* fix model.py

* fix cpp_pass.py

* clear loss.py

* change test file

* fix some test_*.py

* fix adaround.py

* fix evaluator.py

* fix CI bug

* fix CI bug

* fix decode.py

* fix detection.py

* fix ci bug

* rm test_sigmoid_cross_entropy_with_logits_op_ipu.py and fix __init__.py

* fix ci bug

* fix ci BUG

* isort all files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* remove fluid.reduce_sum

* remove fluid.reduce_sum

* modify axis and import paddle

* modify keepdim and out_name

* modift unittest

* modift unittest

* modify CI_static and loss.py

* modify test_mse_loss

* modify static ci

* modify static ci datatype

* add import paddle in test

* fix conflict

* fix conflict

* modify ci

* modify ci

* fix_conflict

* fix bug

* code_style

* remove transpose

* codestyle check

* modify CI_STATIC

* modify CI_STATIC

* modify enable static()

* remove unused import

* fix conflict about stack

* fix conflict about stack

* fix conflict about stack

* endless conflict

* remove reshape in nn.py under fluid

* remove reshape reference

* fix test case

* fix test case in distribution.uniform

* remove fluid reshape reference

* remove apis in fluid.ops

* fix test_activation_nn_grad

* fix circle import error

* fix ops

* fix cos

* fix divide not inplace

* remove lazy-import part

* [CodeStyle][py2][U004] unecessary explicit `object` inheritance in class definition

* fix an increment

* [CodeStyle][E711] use `is`/`is not` for comparison with `None`

* `self.assertTrue($A is None)` -> `self.assertIsNone($A)`

* `self.assertTrue($A is not None)` -> `self.assertIsNotNone($A)`

* `self.assertFalse($A is None)` -> `self.assertIsNotNone($A)`

* `self.assertEqual($A, None)` -> `self.assertIsNone($A)`

* `self.assertNotEqual($A, None)` -> `self.assertIsNotNone($A)`

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

[CodeStyle][NPU] use np.testing.assert_allclose instead of self.assertTrue(np.allclose(...)) (part 1) (#44988)

* autofix

* try resolve precision issues

* revert some changes

* clean some `err_msg`

* 0.0001 -> 1e-4

* update commented assert code

* try to fix some shape errors

* `numpy` -> `np`

* empty commit, trigger kunlun ci, test=kunlun

* empty commit, retrigger kunlun ci, test=kunlun

* empty commit, trigger kunlun ci, try fix npu memcpy_h2d, test=kunlun

* try fix npu import error, test=kunlun

* use yapf to format all python file

* yapf exclude two unittests file for they rely on writing and reading file, and format will break them

* disable diff_py_file because too many diff files cause command following failed

* rename manual_seed to seed

* rename xxx1d-->xxx1D, xxx2d-->xxx2D, xxx3d-->xxx3D

* rename manual_seed --> seed

* do not rename .cc, .cu and .h file

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* disable_static on doc example code

* donot change manual_seed on generator

* add enable_static on sample code

* convert python/paddle/fluid/layers/nn.py to bak

* fix typo

* fix code style

* fix seed to manual_seed when call functions of Generator()

* fix bug

* refine manual seed

* fix ci problem

* fix unittests

* fix unittest

* set is_init_py=false in manual_seed

* fix unittest

* fix bernoulli_op

* fix(unittest): change random_seed to manual_seed

* 🐞fix(unittest): fix manual_seed

* trigger ci

* fix test_sentiment

* fix test_imperative_save_load

* fix test_uniform_random_op

* fix test_uniform_random_op

* fix test_jit_save_load

* merge develop

* fix manual_seed

* fix manual_seed

* use global engine

* use shared_ptr

* fix double free

* fix bug

* fix bug

* fix bug

* fix test bug

* fix test bug

* fix test bug

* fix ci

* Add the first implememtation of fusion_group op #19621 (#3)

* Add the dynamic load of nvrtc, and support runtime compiling of CUDA kernel using nvrtc.
test=develop

* Call CUDA driver api to launch the kernel compiled by nvrtc.
test=develop

* Disable for mac and windows.
test=develop

* Refine the codes to support manually specified num_threads and workload_per_thread.
test=develop

* Refine the CUDA kernel to support large dims.
test=develop

* Add DeviceCodePool to manage all device codes.

* Add the first implementation fusion_group op.

* Add unit-test for fusion_group op.

* Add the check of result.

* Add the check of nvrtc in unit-test.
test=develop

* Add comment to explain the inputs, outputs and features of fusion_group op.
test=develop

* Disable fusion_group op for mac and windows.
test=develop

* Make the compiling of device code return status instead of hanging up.
test=develop

* Add the check of whether there is CUDA driver library, and do not core dump when failing to call the CUDA driver API.

* Unify fusion_group_op's input and output names.
test=develop

* Add the check of CUDA driver library in unittest.
test=develop

* Enable generating code for a given subgraph. #21126 (#4)

* Enable generating code for a given subgraph.

* Support sorting the subgraph.

* Remove the rearange of expressions because we use the sorted subgraph directly.

* Enable generating code for a subgraph which is composed of grad ops.

* Use expression information to check the accuracy in unittest.

* Separate load and store from computation expressions.
test=develop

* Improve the loading statements in generated codes.
test=develop

* Remove unused arguments from formal list.
test=develop

* Enable the detection of subgraph of grad ops.

* Generate code for detected subgraph in fusion_group_pass.

* Add an option in BuildStrategy to enable fusion_group_pass and add unittest.
test=develop

* Fix a bug when checking whether the shape of all inputs are the same.

* Add debug information.

* Remove subgraph_detector from inference/analysis to the common framework/ir directory. (#5)

test=develop

* Call subgraph_detector in fusion_group pass.
test=develop

* Disable fusion_group when WITH_GPU is OFF.
test=develop

* Refine all PADDLE_ENFORCE message.
test=develop

* Fix the case that some inputs are not defined in grad ops, and set op_role for fused op.
test=develop

* Follow review comments.
test=develop

* Refine the cache of program, context and scope in executor.
test=develop

* Refine the unittest test_executor_and_use_program_cache.

* Add the test the PaddingRNN with use_program_cache=True.
test=develop

* Remove a check.
test=develop

* Refine the unittest to check whether it is correct when setting use_program_cache=True.
test=develop

The change includes 3 things:

1. Set CPU_NUM to 1 in the tests because the ParallelExecutor will print warning that CPU_NUM is not set and use default 1.

2. Old tests compare two RNNs, hand written simple RNN and same RNN built by Paddle, but initialized RNN weights in numpy random and Paddle random separately. Fixed it by setting weights and bias values.

3. Also set numpy random seed in the tests. Now the two RNNs diff can be smaller (rtol from 0.1, 0.2 to. 0.01) in the tests.

test=develop

Test PaddingRNN on V100 GPU device.

Test configuration: large model, padding mode (which is the mode using recurrentOp), one GPU.
                   
GPU memory (MiB):   6414 (this PR)     vs   6837 (without this PR)
Speed (steps/s):         10.28 (this PR)    vs    9.89 (without this PR)