remove test_fetch_unmerged (#50619)

python/paddle/fluid/tests/unittests/CMakeLists.txt

@@ -890,7 +890,6 @@ set_tests_properties(
   test_dataloader_keep_order
   test_dataloader_unkeep_order
   test_parallel_ssa_graph_inference_feed_partial_data
-  test_fetch_unmerged
   test_buffer_shared_memory_reuse_pass
   PROPERTIES LABELS "RUN_TYPE=DIST")
 set_tests_properties(
@@ -968,7 +967,6 @@ set_tests_properties(test_inplace_softmax_with_cross_entropy PROPERTIES TIMEOUT
                                                                         120)
 set_tests_properties(test_cross_entropy2_op PROPERTIES TIMEOUT 120)
 set_tests_properties(test_cross_entropy_loss PROPERTIES TIMEOUT 180)
-set_tests_properties(test_fetch_unmerged PROPERTIES TIMEOUT 120)
 set_tests_properties(test_gru_unit_op PROPERTIES TIMEOUT 120)
 set_tests_properties(test_activation_nn_grad PROPERTIES TIMEOUT 200)
 set_tests_properties(test_empty_op PROPERTIES TIMEOUT 120)

python/paddle/fluid/tests/unittests/test_fetch_unmerged.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.
-
-import os
-import unittest
-
-import numpy as np
-
-import paddle
-import paddle.fluid as fluid
-
-os.environ["CPU_NUM"] = "2"
-
-
-class TestFetchUnmerged(unittest.TestCase):
-    def conv_net(self, img, label):
-        conv_pool_1 = fluid.nets.simple_img_conv_pool(
-            input=img,
-            filter_size=5,
-            num_filters=8,
-            pool_size=2,
-            pool_stride=2,
-            pool_type='max',
-            act="relu",
-        )
-        conv_pool_1 = paddle.static.nn.batch_norm(conv_pool_1)
-        conv_pool_2 = fluid.nets.simple_img_conv_pool(
-            input=conv_pool_1,
-            filter_size=5,
-            num_filters=16,
-            pool_size=2,
-            pool_stride=2,
-            pool_type='avg',
-            act="relu",
-        )
-        hidden = paddle.static.nn.fc(x=conv_pool_2, size=32, activation='relu')
-        prediction = paddle.static.nn.fc(
-            x=hidden, size=10, activation='softmax'
-        )
-        loss = paddle.nn.functional.cross_entropy(
-            input=prediction, label=label, reduction='none', use_softmax=False
-        )
-        avg_loss = paddle.mean(loss)
-        return avg_loss, prediction
-
-    def build_program(self, main, startup, is_test):
-        with fluid.unique_name.guard():
-            with fluid.program_guard(main, startup):
-                img = paddle.static.data(
-                    name='image', shape=[-1, 1, 28, 28], dtype='float32'
-                )
-                label = paddle.static.data(
-                    name='label', shape=[-1, 1], dtype='int64'
-                )
-                loss, prediction = self.conv_net(img, label)
-                if not is_test:
-                    opt = fluid.optimizer.Adam(learning_rate=0.001)
-                    opt.minimize(loss)
-        return [img, label], loss, prediction
-
-    def fetch_unmerged(self, use_cuda=True):
-        main_program = fluid.Program()
-        startup_program = fluid.Program()
-        feeds, loss, prediction = self.build_program(
-            main_program, startup_program, False
-        )
-
-        place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-        exe = fluid.Executor(place)
-        exe.run(startup_program)
-
-        build_strategy = fluid.BuildStrategy()
-        binary = fluid.CompiledProgram(main_program).with_data_parallel(
-            loss_name=loss.name, build_strategy=build_strategy
-        )
-
-        iters = 2
-        batch_size = 16
-        train_reader = paddle.batch(
-            paddle.reader.shuffle(paddle.dataset.mnist.train(), buf_size=500),
-            batch_size=batch_size,
-        )
-        feeder = fluid.DataFeeder(feed_list=feeds, place=place)
-
-        device_num = fluid.core.get_cuda_device_count() if use_cuda else 2
-        for _ in range(iters):
-            data = next(train_reader())
-            loss_v, prediction_v = exe.run(
-                binary,
-                feed=feeder.feed(data),
-                fetch_list=[loss, prediction],
-                return_merged=False,
-            )
-            self.assertEqual(np.array(loss_v).shape, (device_num, 1))
-            self.assertEqual(
-                np.array(prediction_v).shape,
-                (device_num, batch_size / device_num, 10),
-            )
-
-        for _ in range(iters):
-            data = next(train_reader())
-            loss_v, prediction_v = exe.run(
-                binary,
-                feed=feeder.feed(data),
-                fetch_list=[loss, prediction],
-                return_merged=True,
-            )
-            self.assertEqual(np.array(loss_v).shape, (device_num,))
-            self.assertEqual(np.array(prediction_v).shape, (batch_size, 10))
-
-    def test_fetch_unmerged(self):
-        if fluid.core.is_compiled_with_cuda():
-            self.fetch_unmerged(use_cuda=True)
-        self.fetch_unmerged(use_cuda=False)
-
-    def test_fetch_unmerged_parallel_graph(self):
-        fluid.core.globals()['FLAGS_enable_parallel_graph'] = True
-        if fluid.core.is_compiled_with_cuda():
-            self.fetch_unmerged(use_cuda=True)
-        self.fetch_unmerged(use_cuda=False)
-        fluid.core.globals()['FLAGS_enable_parallel_graph'] = False
-
-
-if __name__ == '__main__':
-    unittest.main()

tools/parallel_UT_rule.py

@@ -1506,7 +1506,6 @@ FOURTH_HIGH_PARALLEL_JOB_NEW = [
     'test_smooth_l1_loss',
     'test_bilateral_slice_op',
     'test_inplace_abn_op',
-    'test_fetch_unmerged',
     'test_parallel_executor_seresnext_base_gpu',
     'test_parallel_executor_seresnext_with_fuse_all_reduce_gpu',
     'test_parallel_ssa_graph_inference_feed_partial_data',
@@ -2336,7 +2335,6 @@ TETRAD_PARALLEL_JOB = [
     'test_tensorrt_engine',
     'test_load_state_dict_from_old_format',
     'test_fuse_elewise_add_act_pass',
-    'test_fetch_unmerged',
     'test_randint_op',
     'test_standalone_controlflow',
     'test_standalone_multiply_write',

tools/static_mode_white_list.py

@@ -197,7 +197,6 @@ STATIC_MODE_TESTING_LIST = [
     'test_fc_op',
     'test_feed_data_check_shape_type',
     'test_fetch_lod_tensor_array',
-    'test_fetch_unmerged',
     'test_fetch_var',
     'test_fill_any_like_op',
     'test_fill_constant_op',