delete profiler.cuda_profiler (#36524)

* delete profiler.cuda_profiler, test=develop

* delete nvprof, test=develop

* add required: gpu, test=develop

* remove cuda_profiler, test=develop

python/paddle/fluid/profiler.py

@@ -38,72 +38,15 @@ NVPROF_CONFIG = [
 @signature_safe_contextmanager
 def cuda_profiler(output_file, output_mode=None, config=None):
     """
-    The CUDA profiler.
-    
-    This fuctions is used to profile CUDA program by CUDA runtime application
-    programming interface. The profiling result will be written into
-    `output_file`. The users can set the output mode by `output_mode` argument 
-    and set the nvidia profiling config by `config` argument. 
-    
-    After getting the profiling result file, users can use 
-    `NVIDIA Visual Profiler <https://developer.nvidia.com/nvidia-visual-profiler>`_ 
-    to load this output file to visualize results.
-
-    Args:
-        output_file (str) : The output file name, the result will be
-            written into this file.
-        output_mode (str, optional) : The output mode has Key-Value pair format ('kvp') 
-            and Comma separated values format ('csv', default).
-        config (list<str>, optional) : Nvidia profile config. Default config is 
-            ['gpustarttimestamp', 'gpuendtimestamp', 'gridsize3d', 'threadblocksize', 
-            'streamid', 'enableonstart 0', 'conckerneltrace']. For more details, please
-            refer to `Compute Command Line Profiler User Guide <https://developer.download.nvidia.cn/compute/DevZone/docs/html/C/doc/Compute_Command_Line_Profiler_User_Guide.pdf>`_ .
-
-    Raises:
-        ValueError: If `output_mode` is not in ['kvp', 'csv'].
-
-    Examples:
-
-        .. code-block:: python
-
-            import paddle.fluid as fluid
-            import paddle.fluid.profiler as profiler
-            import numpy as np
-
-            epoc = 8
-            dshape = [4, 3, 28, 28]
-            data = fluid.data(name='data', shape=[None, 3, 28, 28], dtype='float32')
-            conv = fluid.layers.conv2d(data, 20, 3, stride=[1, 1], padding=[1, 1])
-
-            place = fluid.CUDAPlace(0)
-            exe = fluid.Executor(place)
-            exe.run(fluid.default_startup_program())
-
-            output_file = 'cuda_profiler.txt'
-            with profiler.cuda_profiler(output_file, 'csv') as nvprof:
-                for i in range(epoc):
-                    input = np.random.random(dshape).astype('float32')
-                    exe.run(fluid.default_main_program(), feed={'data': input})
-            # then use  NVIDIA Visual Profiler (nvvp) to load this output file
-            # to visualize results.
+    API cuda_profiler has been abandoned. If you have relevant requirements, you can use `paddle.utils.profiler.start_profiler` and `paddle.utils.profiler.stop_profiler`. 
+    The relevant reference documents are as follows:
+    <https://www.paddlepaddle.org.cn/documentation/docs/en/api/paddle/utils/profiler/start_profiler_en.html#start-profiler>
+    <https://www.paddlepaddle.org.cn/documentation/docs/en/api/paddle/utils/profiler/stop_profiler_en.html#stop-profiler>
+    <https://www.paddlepaddle.org.cn/documentation/docs/en/advanced_guide/performance_improving/analysis_tools/timeline_en.html>
     """
-    if output_mode is None:
-        output_mode = 'csv'
-    if output_mode not in ['kvp', 'csv']:
-        raise ValueError("The output mode must be 'kvp' or 'csv'.")
-    config = NVPROF_CONFIG if config is None else config
-    config_file = 'nvprof_config_file'
-    with open(config_file, 'wb') as fp:
-        fp.writelines([six.b("%s\n" % item) for item in config])
-    core.nvprof_init(output_file, output_mode, config_file)
-    # Enables profiler collection by the active CUDA profiling tool.
-    core.nvprof_start()
-    try:
-        yield
-    # Disables profiler collection.
-    finally:
-        core.nvprof_stop()
-        os.remove(config_file)
+    raise RuntimeError(
+        "API cuda_profiler has been abandoned. If you have relevant requirements, you can use `paddle.utils.profiler.start_profiler` and `paddle.utils.profiler.stop_profiler`.\nThe relevant reference documents are as follows:\n<https://www.paddlepaddle.org.cn/documentation/docs/en/api/paddle/utils/profiler/start_profiler_en.html#start-profiler>\n<https://www.paddlepaddle.org.cn/documentation/docs/en/api/paddle/utils/profiler/stop_profiler_en.html#stop-profiler>\n<https://www.paddlepaddle.org.cn/documentation/docs/en/advanced_guide/performance_improving/analysis_tools/timeline_en.html>"
+    )
 
 
 @signature_safe_contextmanager
@@ -167,8 +110,7 @@ def npu_profiler(output_file, config=None):
 
 def reset_profiler():
     """
-    Clear the previous time record. This interface does not work for
-    `fluid.profiler.cuda_profiler`, it only works for
+    Clear the previous time record. It works for
     `fluid.profiler.start_profiler`, `fluid.profiler.stop_profiler`,
     and `fluid.profiler.profiler`.
 
@@ -176,6 +118,7 @@ def reset_profiler():
 
         .. code-block:: python
 
+            # required: gpu
             import paddle.fluid as fluid
             import paddle.fluid.profiler as profiler
             with profiler.profiler('CPU', 'total', '/tmp/profile'):
@@ -316,8 +259,7 @@ def profiler(state,
              profile_path='/tmp/profile',
              tracer_option='Default'):
     """
-    The profiler interface. Different from `fluid.profiler.cuda_profiler`, 
-    this profiler can be used to profile both CPU and GPU program.
+    The profiler interface. This profiler can be used to profile both CPU and GPU program.
 
     Args:
         state (str) : The profiling state, which should be one of 'CPU', 'GPU'
@@ -349,9 +291,12 @@ def profiler(state,
 
         .. code-block:: python
 
+            # required: gpu
             import paddle.fluid as fluid
             import paddle.fluid.profiler as profiler
             import numpy as np
+            import paddle
+            paddle.enable_static()
 
             epoc = 8
             dshape = [4, 3, 28, 28]

python/paddle/fluid/tests/unittests/test_nvprof.py

-#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from __future__ import print_function
-
-import unittest
-import os
-import numpy as np
-import paddle.fluid as fluid
-import paddle.fluid.profiler as profiler
-import paddle.fluid.layers as layers
-import paddle.fluid.core as core
-
-
-class TestNVProf(unittest.TestCase):
-    def test_nvprof(self):
-        if not fluid.core.is_compiled_with_cuda():
-            return
-        epoc = 8
-        dshape = [4, 3, 28, 28]
-        data = layers.data(name='data', shape=[3, 28, 28], dtype='float32')
-        conv = layers.conv2d(data, 20, 3, stride=[1, 1], padding=[1, 1])
-
-        place = fluid.CUDAPlace(0)
-        exe = fluid.Executor(place)
-        exe.run(fluid.default_startup_program())
-
-        output_file = 'cuda_profiler.txt'
-        with profiler.cuda_profiler(output_file, 'csv') as nvprof:
-            for i in range(epoc):
-                input = np.random.random(dshape).astype('float32')
-                exe.run(fluid.default_main_program(), feed={'data': input})
-        os.remove(output_file)
-
-
-if __name__ == '__main__':
-    unittest.main()