remove the module: fluid.install_check (#50456)

paddle/scripts/installation_validate.py

@@ -13,7 +13,6 @@
 # limitations under the License.
 
 import paddle as pd
-import paddle.fluid as fluid
 
-fluid.install_check.run_check()
+pd.utils.run_check()
 print(pd.__version__)

python/paddle/fluid/__init__.py

@@ -96,7 +96,6 @@ from .parallel_executor import *
 from . import compiler
 from .compiler import *
 from paddle.fluid.layers.math_op_patch import monkey_patch_variable
-from . import install_check
 from .dygraph.layers import *
 from .dygraph.base import enable_dygraph, disable_dygraph
 from .io import save, load, load_program_state, set_program_state
@@ -161,7 +160,6 @@ __all__ = (
         'profiler',
         'unique_name',
         'Scope',
-        'install_check',
         'save',
         'load',
         '_cuda_synchronize',

python/paddle/fluid/install_check.py

-# Copyright (c) 2019 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.
-
-import os
-import paddle
-from .framework import (
-    Program,
-    program_guard,
-    unique_name,
-    cuda_places,
-    cpu_places,
-)
-from .param_attr import ParamAttr
-from . import layers
-from . import backward
-from .dygraph import Layer
-from . import executor
-from . import optimizer
-from . import core
-from . import compiler
-import logging
-import numpy as np
-
-__all__ = ['run_check']
-
-
-class SimpleLayer(Layer):
-    def __init__(self, input_size):
-        super().__init__()
-        self._linear1 = paddle.nn.Linear(
-            input_size,
-            3,
-            weight_attr=ParamAttr(
-                initializer=paddle.nn.initializer.Constant(value=0.1)
-            ),
-        )
-
-    def forward(self, inputs):
-        x = self._linear1(inputs)
-        x = paddle.sum(x)
-        return x
-
-
-def run_check():
-    """To check whether install is successful
-    This func should not be called only if you need to verify installation
-
-    Examples:
-        .. code-block:: python
-
-            import paddle.fluid as fluid
-            fluid.install_check.run_check()
-
-            # If installed successfully, output may be
-            # Running Verify Fluid Program ...
-            # W0805 04:24:59.496919 35357 device_context.cc:268] Please NOTE: device: 0, CUDA Capability: 70, Driver API Version: 10.2, Runtime API Version: 10.1
-            # W0805 04:24:59.505594 35357 device_context.cc:276] device: 0, cuDNN Version: 7.6.
-            # Your Paddle Fluid works well on SINGLE GPU or CPU.
-            # Your Paddle Fluid works well on MUTIPLE GPU or CPU.
-            # Your Paddle Fluid is installed successfully! Let's start deep Learning with Paddle Fluid now
-    """
-    paddle.enable_static()
-
-    print("Running Verify Fluid Program ... ")
-
-    device_list = []
-    if core.is_compiled_with_cuda():
-        try:
-            core.get_cuda_device_count()
-        except Exception as e:
-            logging.warning(
-                "You are using GPU version Paddle Fluid, But Your CUDA Device is not set properly"
-                "\n Original Error is {}".format(e)
-            )
-            return 0
-        device_list = cuda_places()
-    else:
-        device_list = [core.CPUPlace(), core.CPUPlace()]
-
-    np_inp_single = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
-    inp = []
-    for i in range(len(device_list)):
-        inp.append(np_inp_single)
-    np_inp_muti = np.array(inp)
-    np_inp_muti = np_inp_muti.reshape(len(device_list), 2, 2)
-
-    def test_parallerl_exe():
-        train_prog = Program()
-        startup_prog = Program()
-        scope = core.Scope()
-        with executor.scope_guard(scope):
-            with program_guard(train_prog, startup_prog):
-                with unique_name.guard():
-                    build_strategy = compiler.BuildStrategy()
-                    build_strategy.enable_inplace = True
-                    inp = paddle.static.data(name="inp", shape=[-1, 2, 2])
-                    simple_layer = SimpleLayer(input_size=2)
-                    out = simple_layer(inp)
-                    exe = executor.Executor(
-                        core.CUDAPlace(0)
-                        if core.is_compiled_with_cuda()
-                        and (core.get_cuda_device_count() > 0)
-                        else core.CPUPlace()
-                    )
-                    loss = paddle.mean(out)
-                    loss.persistable = True
-                    optimizer.SGD(learning_rate=0.01).minimize(loss)
-                    startup_prog.random_seed = 1
-                    compiled_prog = compiler.CompiledProgram(
-                        train_prog
-                    ).with_data_parallel(
-                        build_strategy=build_strategy,
-                        loss_name=loss.name,
-                        places=device_list,
-                    )
-                    exe.run(startup_prog)
-
-                    exe.run(
-                        compiled_prog,
-                        feed={inp.name: np_inp_muti},
-                        fetch_list=[loss.name],
-                    )
-
-    def test_simple_exe():
-        train_prog = Program()
-        startup_prog = Program()
-        scope = core.Scope()
-        with executor.scope_guard(scope):
-            with program_guard(train_prog, startup_prog):
-                with unique_name.guard():
-                    inp0 = paddle.static.data(name="inp", shape=[2, 2])
-                    simple_layer0 = SimpleLayer(input_size=2)
-                    out0 = simple_layer0(inp0)
-                    param_grads = backward.append_backward(
-                        out0,
-                        parameter_list=[simple_layer0._linear1.weight.name],
-                    )[0]
-                    exe0 = executor.Executor(
-                        core.CUDAPlace(0)
-                        if core.is_compiled_with_cuda()
-                        and (core.get_cuda_device_count() > 0)
-                        else core.CPUPlace()
-                    )
-                    exe0.run(startup_prog)
-                    exe0.run(
-                        feed={inp0.name: np_inp_single},
-                        fetch_list=[out0.name, param_grads[1].name],
-                    )
-
-    test_simple_exe()
-
-    print("Your Paddle Fluid works well on SINGLE GPU or CPU.")
-    try:
-        test_parallerl_exe()
-        print("Your Paddle Fluid works well on MUTIPLE GPU or CPU.")
-        print(
-            "Your Paddle Fluid is installed successfully! Let's start deep Learning with Paddle Fluid now"
-        )
-    except Exception as e:
-        logging.warning(
-            "Your Paddle Fluid has some problem with multiple GPU. This may be caused by:"
-            "\n 1. There is only 1 or 0 GPU visible on your Device;"
-            "\n 2. No.1 or No.2 GPU or both of them are occupied now"
-            "\n 3. Wrong installation of NVIDIA-NCCL2, please follow instruction on https://github.com/NVIDIA/nccl-tests "
-            "\n to test your NCCL, or reinstall it following https://docs.nvidia.com/deeplearning/sdk/nccl-install-guide/index.html"
-        )
-
-        print("\n Original Error is: {}".format(e))
-        print(
-            "Your Paddle Fluid is installed successfully ONLY for SINGLE GPU or CPU! "
-            "\n Let's start deep Learning with Paddle Fluid now"
-        )
-
-    paddle.disable_static()

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

@@ -19,9 +19,6 @@ import paddle
 
 
 class TestInstallCheck(unittest.TestCase):
-    def test_paddle_fluid(self):
-        paddle.fluid.install_check.run_check()
-
     def test_paddle_utils(self):
         paddle.utils.run_check()