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164 lines
6.5 KiB
164 lines
6.5 KiB
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import paddle
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from .framework import Program, program_guard, unique_name, cuda_places, cpu_places
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from .param_attr import ParamAttr
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from .initializer import Constant
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from . import layers
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from . import backward
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from .dygraph import Layer, nn
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from . import executor
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from . import optimizer
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from . import core
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from . import compiler
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import logging
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import numpy as np
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__all__ = ['run_check']
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class SimpleLayer(Layer):
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def __init__(self, input_size):
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super(SimpleLayer, self).__init__()
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self._linear1 = nn.Linear(
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input_size,
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3,
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param_attr=ParamAttr(initializer=Constant(value=0.1)))
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def forward(self, inputs):
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x = self._linear1(inputs)
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x = layers.reduce_sum(x)
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return x
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def run_check():
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"""To check whether install is successful
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This func should not be called only if you need to verify installation
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Examples:
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.. code-block:: python
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import paddle.fluid as fluid
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fluid.install_check.run_check()
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# If installed successfully, output may be
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# Running Verify Fluid Program ...
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# 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
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# W0805 04:24:59.505594 35357 device_context.cc:276] device: 0, cuDNN Version: 7.6.
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# Your Paddle Fluid works well on SINGLE GPU or CPU.
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# Your Paddle Fluid works well on MUTIPLE GPU or CPU.
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# Your Paddle Fluid is installed successfully! Let's start deep Learning with Paddle Fluid now
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"""
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paddle.enable_static()
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print("Running Verify Fluid Program ... ")
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device_list = []
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if core.is_compiled_with_cuda():
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try:
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core.get_cuda_device_count()
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except Exception as e:
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logging.warning(
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"You are using GPU version Paddle Fluid, But Your CUDA Device is not set properly"
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"\n Original Error is {}".format(e))
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return 0
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device_list = cuda_places()
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else:
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device_list = [core.CPUPlace(), core.CPUPlace()]
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np_inp_single = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
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inp = []
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for i in range(len(device_list)):
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inp.append(np_inp_single)
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np_inp_muti = np.array(inp)
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np_inp_muti = np_inp_muti.reshape(len(device_list), 2, 2)
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def test_parallerl_exe():
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train_prog = Program()
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startup_prog = Program()
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scope = core.Scope()
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with executor.scope_guard(scope):
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with program_guard(train_prog, startup_prog):
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with unique_name.guard():
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build_strategy = compiler.BuildStrategy()
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build_strategy.enable_inplace = True
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inp = layers.data(name="inp", shape=[2, 2])
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simple_layer = SimpleLayer(input_size=2)
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out = simple_layer(inp)
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exe = executor.Executor(
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core.CUDAPlace(0) if core.is_compiled_with_cuda() and
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(core.get_cuda_device_count() > 0) else core.CPUPlace())
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loss = layers.mean(out)
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loss.persistable = True
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optimizer.SGD(learning_rate=0.01).minimize(loss)
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startup_prog.random_seed = 1
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compiled_prog = compiler.CompiledProgram(
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train_prog).with_data_parallel(
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build_strategy=build_strategy,
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loss_name=loss.name,
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places=device_list)
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exe.run(startup_prog)
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exe.run(compiled_prog,
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feed={inp.name: np_inp_muti},
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fetch_list=[loss.name])
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def test_simple_exe():
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train_prog = Program()
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startup_prog = Program()
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scope = core.Scope()
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with executor.scope_guard(scope):
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with program_guard(train_prog, startup_prog):
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with unique_name.guard():
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inp0 = layers.data(
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name="inp", shape=[2, 2], append_batch_size=False)
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simple_layer0 = SimpleLayer(input_size=2)
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out0 = simple_layer0(inp0)
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param_grads = backward.append_backward(
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out0,
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parameter_list=[simple_layer0._linear1.weight.name])[0]
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exe0 = executor.Executor(
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core.CUDAPlace(0) if core.is_compiled_with_cuda() and
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(core.get_cuda_device_count() > 0) else core.CPUPlace())
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exe0.run(startup_prog)
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exe0.run(feed={inp0.name: np_inp_single},
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fetch_list=[out0.name, param_grads[1].name])
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test_simple_exe()
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print("Your Paddle Fluid works well on SINGLE GPU or CPU.")
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try:
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test_parallerl_exe()
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print("Your Paddle Fluid works well on MUTIPLE GPU or CPU.")
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print(
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"Your Paddle Fluid is installed successfully! Let's start deep Learning with Paddle Fluid now"
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)
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except Exception as e:
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logging.warning(
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"Your Paddle Fluid has some problem with multiple GPU. This may be caused by:"
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"\n 1. There is only 1 or 0 GPU visible on your Device;"
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"\n 2. No.1 or No.2 GPU or both of them are occupied now"
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"\n 3. Wrong installation of NVIDIA-NCCL2, please follow instruction on https://github.com/NVIDIA/nccl-tests "
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"\n to test your NCCL, or reinstall it following https://docs.nvidia.com/deeplearning/sdk/nccl-install-guide/index.html"
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)
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print("\n Original Error is: {}".format(e))
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print(
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"Your Paddle Fluid is installed successfully ONLY for SINGLE GPU or CPU! "
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"\n Let's start deep Learning with Paddle Fluid now")
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paddle.disable_static()
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