add auto parallel recursive use case

tests/st/auto_parallel/parallel_strategy_search.py

@@ -295,12 +295,13 @@ class ParallelStrategySearchFactory:
         newest_ckpt_file = find_newest_ckpt_file(ckpt_path)
         return load_checkpoint(newest_ckpt_file)
 
-    def mindspore_auto_parallel_impl(self, dataset, epoch, device_num):
+    def mindspore_auto_parallel_impl(self, dataset, epoch, device_num, auto_parallel_search_mode="dynamic_programming"):
         parallel_mode_net = self.parallel_mode_net
         set_algo_parameters(fully_use_devices=False)
         context.reset_auto_parallel_context()
         context.set_auto_parallel_context(parallel_mode=ParallelMode.AUTO_PARALLEL,
-                                          device_num=device_num)
+                                          device_num=device_num,
+                                          auto_parallel_search_mode=auto_parallel_search_mode)
         self.parallel_ckpt = self._model_train_and_save_ckpt(net=parallel_mode_net,
                                                              dataset=dataset, epoch=epoch)
         context.reset_auto_parallel_context()
@@ -352,3 +353,30 @@ def test_auto_parallel_strategy_search_axis_1_basic():
     fact.mindspore_auto_parallel_impl(dataset=parallel_dataset,
                                       epoch=2, device_num=8)
     fact.checkpoint_cmp(inputs_np=inputs_np)
+
+
+def test_auto_parallel_recursive_strategy_search_axis_1_basic():
+    inputs_np = np.random.randn(32, 3, 224, 224).astype(np.float32)
+    standalone_mode_net = ParallelStrategySearchNet(in_channel=3,
+                                                    out_channel=8, axis=1, input_shape=(32, 4, 110, -1),
+                                                    mul_size=(32, 1, 220, 220), test_size=(32, 4, 110, 880),
+                                                    prelu_size=(1,), transpose_b=True, matmul_size=(1, 12),
+                                                    num_class=12)
+    context.reset_auto_parallel_context()
+    context.set_auto_parallel_context(parallel_mode=ParallelMode.AUTO_PARALLEL)
+    parallel_mode_net = ParallelStrategySearchNet(in_channel=3,
+                                                  out_channel=8, axis=1, input_shape=(32, 4, 110, -1),
+                                                  mul_size=(32, 1, 220, 220), test_size=(32, 4, 110, 880),
+                                                  prelu_size=(1,), transpose_b=True, matmul_size=(1, 12),
+                                                  num_class=12)
+    standalone_dataset = FakeData(size=128, batch_size=32,
+                                  image_size=(3, 224, 224), num_classes=12)
+    fact = ParallelStrategySearchFactory(standalone_mode_net=standalone_mode_net,
+                                         parallel_mode_net=parallel_mode_net)
+    fact.mindspore_standalone_impl(dataset=standalone_dataset, epoch=2)
+    parallel_dataset = FakeData(size=128, batch_size=4,
+                                image_size=(3, 224, 224), use_parallel=True,
+                                num_classes=12)
+    fact.mindspore_auto_parallel_impl(dataset=parallel_dataset,
+                                      epoch=2, device_num=8, auto_parallel_search_mode="recursive_programming")
+    fact.checkpoint_cmp(inputs_np=inputs_np)

tests/st/auto_parallel/run_parallel_recursive_strategy_search.sh

@@ -0,0 +1,52 @@
+#!/bin/bash
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+set -e
+BASE_PATH=$(cd "$(dirname $0)"; pwd)
+CONFIG_PATH=/home/workspace/mindspore_config
+export DEVICE_NUM=8
+export RANK_SIZE=$DEVICE_NUM
+source ${BASE_PATH}/env.sh
+unset SLOG_PRINT_TO_STDOUT
+export MINDSPORE_HCCL_CONFIG_PATH=$CONFIG_PATH/hccl/rank_table_${DEVICE_NUM}p.json
+export LD_LIBRARY_PATH=/usr/local/Ascend/opp/op_impl/built-in/ai_core/tbe/op_tiling:${LD_LIBRARY_PATH}
+export ASCEND_OPP_PATH=/usr/local/Ascend/opp/
+
+process_pid=()
+for((i=0; i<$DEVICE_NUM; i++)); do
+    rm -rf ${BASE_PATH}/parallel_recursive_strategy_search${i}
+    mkdir ${BASE_PATH}/parallel_recursive_strategy_search${i}
+    cp -r ${BASE_PATH}/parallel_strategy_search.py  ${BASE_PATH}/parallel_recursive_strategy_search${i}/
+    cd ${BASE_PATH}/parallel_recursive_strategy_search${i}
+    export RANK_ID=${i}
+    export DEVICE_ID=${i}
+    echo "start training for device $i"
+    env > env$i.log
+    pytest -s -v parallel_strategy_search.py::test_auto_parallel_recursive_strategy_search_axis_1_basic > parallel_recursive_strategy_search$i.log 2>&1 &
+    process_pid[${i}]=`echo $!`
+done
+
+for((i=0; i<${DEVICE_NUM}; i++)); do
+    wait ${process_pid[i]}
+    status=`echo $?`
+    if [ "${status}" != "0" ]; then
+        echo "[ERROR] test_parallel_recursive_strategy_search failed. status: ${status}"
+        exit 1
+    else
+        echo "[INFO] test_parallel_recursive_strategy_search success."
+    fi
+done
+
+exit 0

tests/st/auto_parallel/run_parallel_strategy_search.sh

@@ -34,7 +34,7 @@ for((i=0; i<$DEVICE_NUM; i++)); do
     export DEVICE_ID=${i}
     echo "start training for device $i"
     env > env$i.log
-    pytest -s -v parallel_strategy_search.py > parallel_strategy_search$i.log 2>&1 &
+    pytest -s -v parallel_strategy_search.py::test_auto_parallel_strategy_search_axis_1_basic > parallel_strategy_search$i.log 2>&1 &
     process_pid[${i}]=`echo $!`
 done
 

tests/st/auto_parallel/test_parallel_recursive_strategy_search.py

@@ -0,0 +1,29 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# 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 pytest
+
+
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_single
+def test_sit_parallel_recursive_strategy_search():
+    sh_path = os.path.split(os.path.realpath(__file__))[0]
+    ret = os.system(f"sh {sh_path}/run_parallel_recursive_strategy_search.sh")
+    os.system(
+        f"grep -E 'ERROR|error' "
+        f"{sh_path}/parallel_recursive_strategy_search*/parallel_recursive_strategy_search*log -C 3")
+    assert ret == 0

tests/st/auto_parallel/test_parallel_strategy_search.py

@@ -20,7 +20,7 @@ import pytest
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.env_single
-def test_parallel_strategy_search():
+def test_sit_parallel_strategy_search():
     sh_path = os.path.split(os.path.realpath(__file__))[0]
     ret = os.system(f"sh {sh_path}/run_parallel_strategy_search.sh")
     os.system(f"grep -E 'ERROR|error' {sh_path}/parallel_strategy_search*/parallel_strategy_search*log -C 3")