From a6ef41f38bc963e60818a85ee27a6d2431b455e3 Mon Sep 17 00:00:00 2001 From: chengduo Date: Mon, 3 Sep 2018 15:58:11 +0800 Subject: [PATCH] Fix high level api bug on release-0.15 (#13164) * fix high level API(Inference) bug * patch the unit tests --- python/paddle/fluid/inferencer.py | 7 ++-- .../test_image_classification_resnet.py | 36 ++++++++++++++---- .../test_image_classification_vgg.py | 37 ++++++++++++++----- .../test_recognize_digits_conv.py | 33 ++++++++++++----- .../test_recognize_digits_mlp.py | 37 ++++++++++++++----- 5 files changed, 110 insertions(+), 40 deletions(-) diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py index 3d2ef5661..a9b94a207 100644 --- a/python/paddle/fluid/inferencer.py +++ b/python/paddle/fluid/inferencer.py @@ -98,10 +98,9 @@ class Inferencer(object): raise ValueError( "inputs should be a map of {'input_name': input_var}") - with executor.scope_guard(self.scope): - results = self.exe.run(self.inference_program, - feed=inputs, - fetch_list=[self.predict_var], + with self._prog_and_scope_guard(): + results = self.exe.run(feed=inputs, + fetch_list=[self.predict_var.name], return_numpy=return_numpy) return results diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py index be494a0d3..2e15c224f 100644 --- a/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py +++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py @@ -16,7 +16,9 @@ from __future__ import print_function import paddle import paddle.fluid as fluid +import paddle.fluid.core as core import numpy +import os import cifar10_small_test_set @@ -89,7 +91,7 @@ def optimizer_func(): return fluid.optimizer.Adam(learning_rate=0.001) -def train(use_cuda, train_program, params_dirname): +def train(use_cuda, train_program, parallel, params_dirname): BATCH_SIZE = 128 EPOCH_NUM = 1 @@ -116,7 +118,10 @@ def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() trainer = fluid.Trainer( - train_func=train_program, optimizer_func=optimizer_func, place=place) + train_func=train_program, + optimizer_func=optimizer_func, + place=place, + parallel=parallel) trainer.train( reader=train_reader, @@ -125,10 +130,13 @@ def train(use_cuda, train_program, params_dirname): feed_order=['pixel', 'label']) -def infer(use_cuda, inference_program, params_dirname=None): +def infer(use_cuda, inference_program, parallel, params_dirname=None): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() inferencer = fluid.Inferencer( - infer_func=inference_program, param_path=params_dirname, place=place) + infer_func=inference_program, + param_path=params_dirname, + place=place, + parallel=parallel) # The input's dimension of conv should be 4-D or 5-D. # Use normilized image pixels as input data, which should be in the range @@ -139,22 +147,34 @@ def infer(use_cuda, inference_program, params_dirname=None): print("infer results: ", results) -def main(use_cuda): +def main(use_cuda, parallel): if use_cuda and not fluid.core.is_compiled_with_cuda(): return save_path = "image_classification_resnet.inference.model" + os.environ['CPU_NUM'] = str(4) train( use_cuda=use_cuda, train_program=train_network, - params_dirname=save_path) + params_dirname=save_path, + parallel=parallel) + # FIXME(zcd): in the inference stage, the number of + # input data is one, it is not appropriate to use parallel. + if parallel and use_cuda: + return + + os.environ['CPU_NUM'] = str(1) infer( use_cuda=use_cuda, inference_program=inference_network, - params_dirname=save_path) + params_dirname=save_path, + parallel=parallel) if __name__ == '__main__': for use_cuda in (False, True): - main(use_cuda=use_cuda) + for parallel in (False, True): + if use_cuda and not core.is_compiled_with_cuda(): + continue + main(use_cuda=use_cuda, parallel=parallel) diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py index dbc7bc06c..2f205de1c 100644 --- a/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py +++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py @@ -16,7 +16,9 @@ from __future__ import print_function import paddle import paddle.fluid as fluid +import paddle.fluid.core as core import numpy +import os import cifar10_small_test_set @@ -68,7 +70,7 @@ def optimizer_func(): return fluid.optimizer.Adam(learning_rate=0.001) -def train(use_cuda, train_program, params_dirname): +def train(use_cuda, train_program, parallel, params_dirname): BATCH_SIZE = 128 train_reader = paddle.batch( paddle.reader.shuffle( @@ -93,7 +95,10 @@ def train(use_cuda, train_program, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() trainer = fluid.Trainer( - train_func=train_program, place=place, optimizer_func=optimizer_func) + train_func=train_program, + place=place, + optimizer_func=optimizer_func, + parallel=parallel) trainer.train( reader=train_reader, @@ -102,10 +107,13 @@ def train(use_cuda, train_program, params_dirname): feed_order=['pixel', 'label']) -def infer(use_cuda, inference_program, params_dirname=None): +def infer(use_cuda, inference_program, parallel, params_dirname=None): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() inferencer = fluid.Inferencer( - infer_func=inference_program, param_path=params_dirname, place=place) + infer_func=inference_program, + param_path=params_dirname, + place=place, + parallel=parallel) # The input's dimension of conv should be 4-D or 5-D. # Use normilized image pixels as input data, which should be in the range @@ -116,22 +124,31 @@ def infer(use_cuda, inference_program, params_dirname=None): print("infer results: ", results) -def main(use_cuda): - if use_cuda and not fluid.core.is_compiled_with_cuda(): - return +def main(use_cuda, parallel): save_path = "image_classification_vgg.inference.model" + os.environ['CPU_NUM'] = str(4) train( use_cuda=use_cuda, train_program=train_network, - params_dirname=save_path) + params_dirname=save_path, + parallel=parallel) + # FIXME(zcd): in the inference stage, the number of + # input data is one, it is not appropriate to use parallel. + if parallel and use_cuda: + return + os.environ['CPU_NUM'] = str(1) infer( use_cuda=use_cuda, inference_program=inference_network, - params_dirname=save_path) + params_dirname=save_path, + parallel=parallel) if __name__ == '__main__': for use_cuda in (False, True): - main(use_cuda=use_cuda) + for parallel in (False, True): + if use_cuda and not core.is_compiled_with_cuda(): + continue + main(use_cuda=use_cuda, parallel=parallel) diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py index 187bef1b0..a5adf6815 100644 --- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py +++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py @@ -64,14 +64,14 @@ def optimizer_func(): return fluid.optimizer.Adam(learning_rate=0.001) -def train(use_cuda, train_program, params_dirname): +def train(use_cuda, train_program, parallel, params_dirname): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() trainer = fluid.Trainer( train_func=train_program, place=place, optimizer_func=optimizer_func, - parallel=True) + parallel=parallel) def event_handler(event): if isinstance(event, fluid.EndEpochEvent): @@ -108,11 +108,14 @@ def train(use_cuda, train_program, params_dirname): feed_order=['img', 'label']) -def infer(use_cuda, inference_program, params_dirname=None): +def infer(use_cuda, inference_program, parallel, params_dirname=None): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() inferencer = fluid.Inferencer( - infer_func=inference_program, param_path=params_dirname, place=place) + infer_func=inference_program, + param_path=params_dirname, + place=place, + parallel=parallel) batch_size = 1 tensor_img = numpy.random.uniform(-1.0, 1.0, @@ -123,20 +126,32 @@ def infer(use_cuda, inference_program, params_dirname=None): print("infer results: ", results[0]) -def main(use_cuda): +def main(use_cuda, parallel): params_dirname = "recognize_digits_conv.inference.model" # call train() with is_local argument to run distributed train + os.environ['CPU_NUM'] = str(4) train( use_cuda=use_cuda, train_program=train_program, - params_dirname=params_dirname) + params_dirname=params_dirname, + parallel=parallel) + + # FIXME(zcd): in the inference stage, the number of + # input data is one, it is not appropriate to use parallel. + if parallel and use_cuda: + return + os.environ['CPU_NUM'] = str(1) infer( use_cuda=use_cuda, inference_program=inference_program, - params_dirname=params_dirname) + params_dirname=params_dirname, + parallel=parallel) if __name__ == '__main__': - # for use_cuda in (False, True): - main(use_cuda=core.is_compiled_with_cuda()) + for use_cuda in (False, True): + for parallel in (False, True): + if use_cuda and not core.is_compiled_with_cuda(): + continue + main(use_cuda=use_cuda, parallel=parallel) diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py index b95e7db12..e7d8b23b3 100644 --- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py +++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py @@ -16,6 +16,7 @@ from __future__ import print_function import argparse import paddle.fluid as fluid +import paddle.fluid.core as core import paddle import sys import numpy @@ -50,11 +51,14 @@ def optimizer_func(): return fluid.optimizer.Adam(learning_rate=0.001) -def train(use_cuda, train_program, params_dirname): +def train(use_cuda, train_program, params_dirname, parallel): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() trainer = fluid.Trainer( - train_func=train_program, place=place, optimizer_func=optimizer_func) + train_func=train_program, + place=place, + optimizer_func=optimizer_func, + parallel=parallel) def event_handler(event): if isinstance(event, fluid.EndEpochEvent): @@ -86,11 +90,14 @@ def train(use_cuda, train_program, params_dirname): feed_order=['img', 'label']) -def infer(use_cuda, inference_program, params_dirname=None): +def infer(use_cuda, inference_program, parallel, params_dirname=None): place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() inferencer = fluid.Inferencer( - infer_func=inference_program, param_path=params_dirname, place=place) + infer_func=inference_program, + param_path=params_dirname, + place=place, + parallel=parallel) batch_size = 1 tensor_img = numpy.random.uniform(-1.0, 1.0, @@ -101,20 +108,32 @@ def infer(use_cuda, inference_program, params_dirname=None): print("infer results: ", results[0]) -def main(use_cuda): +def main(use_cuda, parallel): params_dirname = "recognize_digits_mlp.inference.model" # call train() with is_local argument to run distributed train + os.environ['CPU_NUM'] = str(4) train( use_cuda=use_cuda, train_program=train_program, - params_dirname=params_dirname) + params_dirname=params_dirname, + parallel=parallel) + + # FIXME(zcd): in the inference stage, the number of + # input data is one, it is not appropriate to use parallel. + if parallel and use_cuda: + return + os.environ['CPU_NUM'] = str(1) infer( use_cuda=use_cuda, inference_program=inference_program, - params_dirname=params_dirname) + params_dirname=params_dirname, + parallel=parallel) if __name__ == '__main__': - # for use_cuda in (False, True): - main(use_cuda=False) + for use_cuda in (False, True): + for parallel in (False, True): + if use_cuda and not core.is_compiled_with_cuda(): + continue + main(use_cuda=use_cuda, parallel=parallel) -- GitLab