From 1b83b435ec03063af2391b39c0a1ce719137702b Mon Sep 17 00:00:00 2001 From: root <18013846960@189.cn> Date: Tue, 29 Mar 2022 21:23:08 +0800 Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E5=AD=97=E7=AC=A6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../ Memnet_ID1085_for_ACL/modelarts_entry.py | 8 ++++---- .../cv/ Memnet_ID1085_for_ACL/npu_train.sh | 18 +++++++++--------- .../ Memnet_ID1085_for_ACL/train_testcase.sh | 8 ++++---- .../DDcGAN_ID2123_for_ACL/modelarts_entry.py | 8 ++++---- .../contrib/cv/DDcGAN_ID2123_for_ACL/om_run.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../cv/ADDA_ID1026_for_TensorFlow/npu_train.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../train_testcase.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../npu_train.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../npu_train.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../train_testcase.sh | 18 +++++++++--------- .../npu_train.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../npu_train.sh | 18 +++++++++--------- .../train_testcase.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../Memnet_ID1085_for_TensorFlow/npu_train.sh | 18 +++++++++--------- .../train_testcase.sh | 8 ++++---- .../Code/modelarts_entry.py | 8 ++++---- .../Code/npu_train.sh | 18 +++++++++--------- .../src/tools_pix2pose/modelarts_entry.py | 8 ++++---- .../src/tools_pix2pose/npu_train.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../npu_train.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../train_testcase.sh | 18 +++++++++--------- .../modelarts_entry.py | 8 ++++---- .../npu_freeze.sh | 18 +++++++++--------- .../npu_train.sh | 18 +++++++++--------- 33 files changed, 217 insertions(+), 217 deletions(-) diff --git a/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/modelarts_entry.py b/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/modelarts_entry.py index 55875465b..b65b55a7d 100644 --- a/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/modelarts_entry.py +++ b/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/modelarts_entry.py @@ -21,17 +21,17 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/npu_train.sh b/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/npu_train.sh index 0b02335a4..1be2a3f38 100644 --- a/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/npu_train.sh +++ b/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/npu_train.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -40,9 +40,9 @@ env > ${output_path}/my_env.log python3.7 ${code_dir}/main.py --output_dir=${output_path} --phase=train --training_set=${dataset_path}/VOC0712.tfrecords --batch_size=1 --training_steps=100000 --summary_steps=50 --checkpoint_steps=1000 --save_steps=500 if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -50,10 +50,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/train_testcase.sh b/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/train_testcase.sh index 685244fad..3f1ad8dbd 100644 --- a/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/train_testcase.sh +++ b/ACL_TensorFlow/contrib/cv/ Memnet_ID1085_for_ACL/train_testcase.sh @@ -17,9 +17,9 @@ output_path=./result/ python3.7 ./main.py --output_dir=${output_path} --phase=train --training_set=${dataset_path}/BSD.tfrecords --batch_size=1 --training_steps=1000 --summary_steps=50 --checkpoint_steps=100 --save_steps=50 if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -27,10 +27,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" \ No newline at end of file diff --git a/ACL_TensorFlow/contrib/cv/DDcGAN_ID2123_for_ACL/modelarts_entry.py b/ACL_TensorFlow/contrib/cv/DDcGAN_ID2123_for_ACL/modelarts_entry.py index 16fab88c2..1c77c27b0 100644 --- a/ACL_TensorFlow/contrib/cv/DDcGAN_ID2123_for_ACL/modelarts_entry.py +++ b/ACL_TensorFlow/contrib/cv/DDcGAN_ID2123_for_ACL/modelarts_entry.py @@ -37,17 +37,17 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/ACL_TensorFlow/contrib/cv/DDcGAN_ID2123_for_ACL/om_run.sh b/ACL_TensorFlow/contrib/cv/DDcGAN_ID2123_for_ACL/om_run.sh index d66734e69..33e275b1c 100644 --- a/ACL_TensorFlow/contrib/cv/DDcGAN_ID2123_for_ACL/om_run.sh +++ b/ACL_TensorFlow/contrib/cv/DDcGAN_ID2123_for_ACL/om_run.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #pip install scipy==1.2.1 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -45,9 +45,9 @@ python3.7 ${code_dir}/ModelCkptToPb.py ${dataset_path} ${output_path} if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -55,10 +55,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/ADDA_ID1026_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/ADDA_ID1026_for_TensorFlow/modelarts_entry.py index 79207c134..8122f6783 100644 --- a/TensorFlow/contrib/cv/ADDA_ID1026_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/ADDA_ID1026_for_TensorFlow/modelarts_entry.py @@ -42,17 +42,17 @@ config = parser.parse_args() mox.file.copy_parallel(src_url=config.data_url, dst_url="/home/ma-user/modelarts/workspace/device0/data") -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/ADDA_ID1026_for_TensorFlow/npu_train.sh b/TensorFlow/contrib/cv/ADDA_ID1026_for_TensorFlow/npu_train.sh index 500d7e54b..782265a94 100644 --- a/TensorFlow/contrib/cv/ADDA_ID1026_for_TensorFlow/npu_train.sh +++ b/TensorFlow/contrib/cv/ADDA_ID1026_for_TensorFlow/npu_train.sh @@ -39,23 +39,23 @@ pip install tflearn pip install colorlog #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -162,9 +162,9 @@ python ${code_dir}/tools/eval_classification.py usps1800 train lenet snapshot/ad if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -175,10 +175,10 @@ cp -r ${work_dir} ${output_path} cp -r '/cache/profiling' ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/DDCGAN_ID2123_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/DDCGAN_ID2123_for_TensorFlow/modelarts_entry.py index 62b4451dc..73212a4da 100644 --- a/TensorFlow/contrib/cv/DDCGAN_ID2123_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/DDCGAN_ID2123_for_TensorFlow/modelarts_entry.py @@ -37,18 +37,18 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/DDCGAN_ID2123_for_TensorFlow/train_testcase.sh b/TensorFlow/contrib/cv/DDCGAN_ID2123_for_TensorFlow/train_testcase.sh index ae164c7ca..388fc1594 100644 --- a/TensorFlow/contrib/cv/DDCGAN_ID2123_for_TensorFlow/train_testcase.sh +++ b/TensorFlow/contrib/cv/DDCGAN_ID2123_for_TensorFlow/train_testcase.sh @@ -7,23 +7,23 @@ dataset_path=$3 output_path=$4 #pip3 install scipy==1.2.1 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -42,9 +42,9 @@ env > ${output_path}/my_env.log python3.7 ${code_dir}/main.py ${dataset_path} ${output_path} if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -52,10 +52,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/Deep-SLR_ID2122_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/Deep-SLR_ID2122_for_TensorFlow/modelarts_entry.py index cd94c7a9d..ba1f4ece9 100644 --- a/TensorFlow/contrib/cv/Deep-SLR_ID2122_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/Deep-SLR_ID2122_for_TensorFlow/modelarts_entry.py @@ -38,18 +38,18 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # Execute training script shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/Deep-SLR_ID2122_for_TensorFlow/npu_train.sh b/TensorFlow/contrib/cv/Deep-SLR_ID2122_for_TensorFlow/npu_train.sh index 64245cf4f..52df7cb06 100644 --- a/TensorFlow/contrib/cv/Deep-SLR_ID2122_for_TensorFlow/npu_train.sh +++ b/TensorFlow/contrib/cv/Deep-SLR_ID2122_for_TensorFlow/npu_train.sh @@ -32,23 +32,23 @@ dataset_path=$3 output_path=$4 ############# Confirm the input directories and files before training ######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -66,9 +66,9 @@ env >${output_path}/my_env.log ### Modify according to the commands to run python3.7 ${code_dir}/trn_HDSLR_parallel_mri.py --data_path=${dataset_path} --output_path=${output_path} --steps=100 if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ###### Save the contents to output_path ###### @@ -76,10 +76,10 @@ fi cp -r ${work_dir} ${output_path} ###### Print directory and file confirmation after training ###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/DeepFaceLab_ID2017_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/DeepFaceLab_ID2017_for_TensorFlow/modelarts_entry.py index db2ce055b..ff375b6d9 100644 --- a/TensorFlow/contrib/cv/DeepFaceLab_ID2017_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/DeepFaceLab_ID2017_for_TensorFlow/modelarts_entry.py @@ -35,17 +35,17 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/DeepFaceLab_ID2017_for_TensorFlow/npu_train.sh b/TensorFlow/contrib/cv/DeepFaceLab_ID2017_for_TensorFlow/npu_train.sh index 0fe7a3c2e..94a405efe 100644 --- a/TensorFlow/contrib/cv/DeepFaceLab_ID2017_for_TensorFlow/npu_train.sh +++ b/TensorFlow/contrib/cv/DeepFaceLab_ID2017_for_TensorFlow/npu_train.sh @@ -7,23 +7,23 @@ output_path=$4 echo "$code_dir" echo "$output_path" #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -51,9 +51,9 @@ python3.7 ${code_dir}/train.py \ --model_dir=${output_path}model if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -61,10 +61,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/FaceBoxes_ID1074_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/FaceBoxes_ID1074_for_TensorFlow/modelarts_entry.py index 6d445b945..8bec6c521 100644 --- a/TensorFlow/contrib/cv/FaceBoxes_ID1074_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/FaceBoxes_ID1074_for_TensorFlow/modelarts_entry.py @@ -37,21 +37,21 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() current_path = os.path.dirname(__file__) sys.path.append(current_path + "/") -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") shell_cmd = ("bash %s/train_testcase.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/FaceBoxes_ID1074_for_TensorFlow/train_testcase.sh b/TensorFlow/contrib/cv/FaceBoxes_ID1074_for_TensorFlow/train_testcase.sh index 4204e825a..ea2c7a70a 100644 --- a/TensorFlow/contrib/cv/FaceBoxes_ID1074_for_TensorFlow/train_testcase.sh +++ b/TensorFlow/contrib/cv/FaceBoxes_ID1074_for_TensorFlow/train_testcase.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -41,9 +41,9 @@ env > ${output_path}/my_env.log python3.7 ${code_dir}/train.py --data_path=${dataset_path} --output_path=${output_path} --step=25 if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -51,10 +51,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/npu_train.sh b/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/npu_train.sh index fea104208..d92445f1a 100644 --- a/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/npu_train.sh +++ b/TensorFlow/contrib/cv/HybridSN_ID1160_for_TensorFlow/npu_train.sh @@ -38,23 +38,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -74,9 +74,9 @@ python3.7 /home/ma-user/modelarts/user-job-dir/code/Hybrid-Spectral-Net.py #--data_path=${D:/PytorchProgram/HybridSN-master/data} --output_path=${D:/PytorchProgram/HybridSN-master/data} --steps=100 if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -84,10 +84,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/LEARNING-TO-LEARN_ID2075_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/LEARNING-TO-LEARN_ID2075_for_TensorFlow/modelarts_entry.py index 30d2b9027..f7b8344f7 100644 --- a/TensorFlow/contrib/cv/LEARNING-TO-LEARN_ID2075_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/LEARNING-TO-LEARN_ID2075_for_TensorFlow/modelarts_entry.py @@ -21,17 +21,17 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/LEARNING-TO-LEARN_ID2075_for_TensorFlow/npu_train.sh b/TensorFlow/contrib/cv/LEARNING-TO-LEARN_ID2075_for_TensorFlow/npu_train.sh index bd30a98d6..072e2d6ab 100644 --- a/TensorFlow/contrib/cv/LEARNING-TO-LEARN_ID2075_for_TensorFlow/npu_train.sh +++ b/TensorFlow/contrib/cv/LEARNING-TO-LEARN_ID2075_for_TensorFlow/npu_train.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -44,9 +44,9 @@ env > ${output_path}/my_env.log python3.7 ${code_dir}/evaluate3.py --data_path=${dataset_path} --output_path=${output_path} --steps ==100 if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -54,10 +54,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/LEARNING-TO-SEE-IN-THE-DARK_ID2069_for_TensorFlow/train_testcase.sh b/TensorFlow/contrib/cv/LEARNING-TO-SEE-IN-THE-DARK_ID2069_for_TensorFlow/train_testcase.sh index 38084af7a..5e8372f95 100644 --- a/TensorFlow/contrib/cv/LEARNING-TO-SEE-IN-THE-DARK_ID2069_for_TensorFlow/train_testcase.sh +++ b/TensorFlow/contrib/cv/LEARNING-TO-SEE-IN-THE-DARK_ID2069_for_TensorFlow/train_testcase.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -46,9 +46,9 @@ env > ${output_path}/my_env.log python3.7 ${code_dir}/train_Sony.py if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -56,10 +56,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/modelarts_entry.py index 30d2b9027..f7b8344f7 100644 --- a/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/modelarts_entry.py @@ -21,17 +21,17 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/npu_train.sh b/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/npu_train.sh index 0b02335a4..1be2a3f38 100644 --- a/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/npu_train.sh +++ b/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/npu_train.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -40,9 +40,9 @@ env > ${output_path}/my_env.log python3.7 ${code_dir}/main.py --output_dir=${output_path} --phase=train --training_set=${dataset_path}/VOC0712.tfrecords --batch_size=1 --training_steps=100000 --summary_steps=50 --checkpoint_steps=1000 --save_steps=500 if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -50,10 +50,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/train_testcase.sh b/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/train_testcase.sh index 685244fad..3f1ad8dbd 100644 --- a/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/train_testcase.sh +++ b/TensorFlow/contrib/cv/Memnet/Memnet_ID1085_for_TensorFlow/train_testcase.sh @@ -17,9 +17,9 @@ output_path=./result/ python3.7 ./main.py --output_dir=${output_path} --phase=train --training_set=${dataset_path}/BSD.tfrecords --batch_size=1 --training_steps=1000 --summary_steps=50 --checkpoint_steps=100 --save_steps=50 if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -27,10 +27,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" \ No newline at end of file diff --git a/TensorFlow/contrib/cv/Pix2Vox_ID1284_for_TensorFlow/Code/modelarts_entry.py b/TensorFlow/contrib/cv/Pix2Vox_ID1284_for_TensorFlow/Code/modelarts_entry.py index d871c7ae7..4fb8aca77 100644 --- a/TensorFlow/contrib/cv/Pix2Vox_ID1284_for_TensorFlow/Code/modelarts_entry.py +++ b/TensorFlow/contrib/cv/Pix2Vox_ID1284_for_TensorFlow/Code/modelarts_entry.py @@ -38,17 +38,17 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/Pix2Vox_ID1284_for_TensorFlow/Code/npu_train.sh b/TensorFlow/contrib/cv/Pix2Vox_ID1284_for_TensorFlow/Code/npu_train.sh index 2d487f482..a91aac698 100644 --- a/TensorFlow/contrib/cv/Pix2Vox_ID1284_for_TensorFlow/Code/npu_train.sh +++ b/TensorFlow/contrib/cv/Pix2Vox_ID1284_for_TensorFlow/Code/npu_train.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -40,9 +40,9 @@ env > ${output_path}/my_env.log python3.7 ${code_dir}/main_AttSets.py --data_url=${dataset_path} --train_url=${output_path} if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -50,10 +50,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow/src/tools_pix2pose/modelarts_entry.py b/TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow/src/tools_pix2pose/modelarts_entry.py index db2ce055b..ff375b6d9 100644 --- a/TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow/src/tools_pix2pose/modelarts_entry.py +++ b/TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow/src/tools_pix2pose/modelarts_entry.py @@ -35,17 +35,17 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow/src/tools_pix2pose/npu_train.sh b/TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow/src/tools_pix2pose/npu_train.sh index 1bc8c9e1b..f7c2b1e04 100644 --- a/TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow/src/tools_pix2pose/npu_train.sh +++ b/TensorFlow/contrib/cv/Pix2pose_ID1164_for_TensorFlow/src/tools_pix2pose/npu_train.sh @@ -33,23 +33,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -90,9 +90,9 @@ python3.7 ${code_dir}/scripts/eval_calc_errors.py --n_top=-1 --error_type=vsd - if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -100,10 +100,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/RANDLA-NET_ID0850_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/RANDLA-NET_ID0850_for_TensorFlow/modelarts_entry.py index 384453dca..ee8f4d621 100644 --- a/TensorFlow/contrib/cv/RANDLA-NET_ID0850_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/RANDLA-NET_ID0850_for_TensorFlow/modelarts_entry.py @@ -41,17 +41,17 @@ parser.add_argument("--data_url", type=str, default="s3://randla-net/data_retry/ parser.add_argument("--train_url", type=str, default="s3:///randla-net/train_out_npu/") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/RANDLA-NET_ID0850_for_TensorFlow/npu_train.sh b/TensorFlow/contrib/cv/RANDLA-NET_ID0850_for_TensorFlow/npu_train.sh index 6adefc812..0a169ade8 100644 --- a/TensorFlow/contrib/cv/RANDLA-NET_ID0850_for_TensorFlow/npu_train.sh +++ b/TensorFlow/contrib/cv/RANDLA-NET_ID0850_for_TensorFlow/npu_train.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -42,9 +42,9 @@ python3.7 ${code_dir}/main_S3DIS.py --data_path=${dataset_path} --output_path=${ python3.7 ${code_dir}/main_S3DIS.py --data_path=${dataset_path} --output_path=${output_path} --mode train --test_area 3 --train_steps 1000 --batch_size 3 --val_steps 100 --val_batch_size 3 --max_epoch 3 if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -52,10 +52,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/fusiongan/FusionGAN_ID2124_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/fusiongan/FusionGAN_ID2124_for_TensorFlow/modelarts_entry.py index 67e317add..e9842ead2 100644 --- a/TensorFlow/contrib/cv/fusiongan/FusionGAN_ID2124_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/fusiongan/FusionGAN_ID2124_for_TensorFlow/modelarts_entry.py @@ -23,17 +23,17 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") # 执行训练脚本 shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") diff --git a/TensorFlow/contrib/cv/fusiongan/FusionGAN_ID2124_for_TensorFlow/train_testcase.sh b/TensorFlow/contrib/cv/fusiongan/FusionGAN_ID2124_for_TensorFlow/train_testcase.sh index 37f5ba742..224c54596 100644 --- a/TensorFlow/contrib/cv/fusiongan/FusionGAN_ID2124_for_TensorFlow/train_testcase.sh +++ b/TensorFlow/contrib/cv/fusiongan/FusionGAN_ID2124_for_TensorFlow/train_testcase.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -40,9 +40,9 @@ env > ${output_path}/my_env.log python3.7 ${code_dir}/test_one_image.py ${dataset_path} ${output_path} if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -50,10 +50,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" diff --git a/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/modelarts_entry.py b/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/modelarts_entry.py index 2a1708919..1c9c4442a 100644 --- a/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/modelarts_entry.py +++ b/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/modelarts_entry.py @@ -36,20 +36,20 @@ parser.add_argument("--data_url", type=str, default="/cache/dataset") parser.add_argument("--train_url", type=str, default="/cache/output") config = parser.parse_args() -print("[CANN-ZhongZhi] code_dir path is [%s]" % (sys.path[0])) +print("[CANN-Modelzoo] code_dir path is [%s]" % (sys.path[0])) code_dir = sys.path[0] -print("[CANN-ZhongZhi] work_dir path is [%s]" % (os.getcwd())) +print("[CANN-Modelzoo] work_dir path is [%s]" % (os.getcwd())) work_dir = os.getcwd() -print("[CANN-ZhongZhi] start run train shell") +print("[CANN-Modelzoo] start run train shell") ## [Training] shell_cmd = ("bash %s/npu_train.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) ## [Freeze Graph] #shell_cmd = ("bash %s/npu_freeze.sh %s %s %s %s " % (code_dir, code_dir, work_dir, config.data_url, config.train_url)) os.system(shell_cmd) -print("[CANN-ZhongZhi] finish run train shell") +print("[CANN-Modelzoo] finish run train shell") #import moxing as mox #import precision_tool.config as CONFIG diff --git a/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/npu_freeze.sh b/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/npu_freeze.sh index 3fb6c8504..ec2bbf921 100644 --- a/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/npu_freeze.sh +++ b/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/npu_freeze.sh @@ -6,23 +6,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -73,9 +73,9 @@ python3.7 ${code_dir}/main.py --data_path=${dataset_path} --output_path=${output if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -83,10 +83,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" \ No newline at end of file diff --git a/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/npu_train.sh b/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/npu_train.sh index 64234475f..cec5059cb 100644 --- a/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/npu_train.sh +++ b/TensorFlow/contrib/cv/meta-pseudo-labels/META_PSEUDO_LABEL_ID2024_for_TensorFlow/npu_train.sh @@ -34,23 +34,23 @@ dataset_path=$3 output_path=$4 #############训练前输入目录文件确认######################### -echo "[CANN-ZhongZhi] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" +echo "[CANN-Modelzoo] before train - list my run files[/usr/local/Ascend/ascend-toolkit]:" ls -al /usr/local/Ascend/ascend-toolkit echo "" -echo "[CANN-ZhongZhi] before train - list my code files[${code_dir}]:" +echo "[CANN-Modelzoo] before train - list my code files[${code_dir}]:" ls -al ${code_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] before train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] before train - list my dataset files[${dataset_path}]:" +echo "[CANN-Modelzoo] before train - list my dataset files[${dataset_path}]:" ls -al ${dataset_path} echo "" -echo "[CANN-ZhongZhi] before train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] before train - list my output files[${output_path}]:" ls -al ${output_path} echo "" @@ -101,9 +101,9 @@ python3.7 ${code_dir}/main.py --data_path=${dataset_path} --output_path=${output if [ $? -eq 0 ]; then - echo "[CANN-ZhongZhi] train return success" + echo "[CANN-Modelzoo] train return success" else - echo "[CANN-ZhongZhi] train return failed" + echo "[CANN-Modelzoo] train return failed" fi ######训练后把需要备份的内容保存到output_path###### @@ -111,10 +111,10 @@ fi cp -r ${work_dir} ${output_path} ######训练后输出目录文件确认###### -echo "[CANN-ZhongZhi] after train - list my work files[${work_dir}]:" +echo "[CANN-Modelzoo] after train - list my work files[${work_dir}]:" ls -al ${work_dir} echo "" -echo "[CANN-ZhongZhi] after train - list my output files[${output_path}]:" +echo "[CANN-Modelzoo] after train - list my output files[${output_path}]:" ls -al ${output_path} echo "" -- Gitee