!17046 add modelzoo network retinaface_resnet50 testcase

From: @anzhengqi
Reviewed-by: @c_34,@wuxuejian
Signed-off-by: @c_34

model_zoo/official/cv/retinaface_resnet50/scripts/run_distribute_gpu_train.sh

@@ -23,5 +23,5 @@ echo "==========================================================================
 RANK_SIZE=$1
 export CUDA_VISIBLE_DEVICES="$2"
 
-mpirun --allow-run-as-root -n $RANK_SIZE \
+mpirun --allow-run-as-root -n $RANK_SIZE --output-filename log_output --merge-stderr-to-stdout \
     python train.py > train.log 2>&1 &

model_zoo/official/cv/retinaface_resnet50/src/dataset.py

@@ -56,6 +56,19 @@ class WiderFace():
         # add the last label
         self.labels_list.append(labels)
 
+        # del bbox which width is zero or height is zero
+        for i in range(len(self.labels_list) - 1, -1, -1):
+            labels = self.labels_list[i]
+            for j in range(len(labels) - 1, -1, -1):
+                label = labels[j]
+                if label[2] <= 0 or label[3] <= 0:
+                    labels.pop(j)
+            if not labels:
+                self.images_list.pop(i)
+                self.labels_list.pop(i)
+            else:
+                self.labels_list[i] = labels
+
     def __len__(self):
         return len(self.images_list)
 

tests/st/model_zoo_tests/retinaface_resnet50/test_retinaface_resnet50.py

@@ -0,0 +1,66 @@
+# Copyright 2021 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
+
+from tests.st.model_zoo_tests import utils
+
+
+@pytest.mark.level1
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_single
+def test_retinaface_resnet50():
+    cur_path = os.path.dirname(os.path.abspath(__file__))
+    model_path = "{}/../../../../model_zoo/official/cv".format(cur_path)
+    model_name = "retinaface_resnet50"
+    utils.copy_files(model_path, cur_path, model_name)
+    cur_model_path = os.path.join(cur_path, model_name)
+    train_data_path = os.path.join(utils.data_root, "widerface/label.txt")
+    pretrain_ckpt_path = os.path.join(utils.ckpt_root, "resnet/resnet-90_4p.ckpt")
+    weight_ckpt_path = os.path.join(utils.ckpt_root, "retinaface_resnet/retinaface_res50_epoch_0.ckpt")
+    if not os.path.exists(weight_ckpt_path):
+        raise RuntimeError("file {} not exist.".format(weight_ckpt_path))
+    if not os.path.exists(pretrain_ckpt_path):
+        raise RuntimeError("file {} not exist.".format(pretrain_ckpt_path))
+    old_list = ["'epoch': 100,",
+                "'save_checkpoint_steps': 2000,",
+                "'training_dataset': './data/widerface/train/label.txt',",
+                "'pretrain_path': './data/res50_pretrain.ckpt'",
+                "'resume_net': None,"]
+    new_list = ["'epoch': 1,",
+                "'save_checkpoint_steps': 402,",
+                "'training_dataset': '{}',".format(train_data_path),
+                "'pretrain_path': '{}'".format(pretrain_ckpt_path),
+                "'resume_net': '{}',".format(weight_ckpt_path)]
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "src/config.py"))
+    old_list = ["sink_mode=True", "model.train(max_epoch,"]
+    new_list = ["sink_mode=True, sink_size=100", "model.train(4,"]
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "train.py"))
+    exec_network_shell = "cd retinaface_resnet50; bash scripts/run_distribute_gpu_train.sh 4 1,2,3,4"
+    os.system(exec_network_shell)
+    cmd = "ps -ef | grep train.py | grep -v grep"
+    ret = utils.process_check(120, cmd)
+    if not ret:
+        cmd = "{} | awk -F' ' '{{print $2}}' | xargs kill -9".format(cmd)
+        os.system(cmd)
+    assert ret
+    log_file = os.path.join(cur_model_path, "train.log")
+    pattern = r"per step time: ([\d\.]+) ms"
+    per_step_time_list = utils.parse_log_file(pattern, log_file)[4:]
+    print("per_step_time_list is", per_step_time_list)
+    assert sum(per_step_time_list)/len(per_step_time_list) < 673.7
+    loss_list = utils.get_loss_data_list(log_file)[-4:]
+    print("loss_list is", loss_list)
+    assert sum(loss_list) / len(loss_list) < 12.57