diff --git a/mindspore/lite/test/config/models_ms_train.cfg b/mindspore/lite/test/config/models_ms_train.cfg index b8d65866245..503366a634a 100644 --- a/mindspore/lite/test/config/models_ms_train.cfg +++ b/mindspore/lite/test/config/models_ms_train.cfg @@ -44,3 +44,4 @@ unified_api code_example train_lenet code_example train_lenet_java code_example # LAST +test_resize inputShapes 16,10,10,1:16,10,10,1 0.5 diff --git a/mindspore/lite/test/st/scripts/run_net_train.sh b/mindspore/lite/test/st/scripts/run_net_train.sh index 870c53c26ac..40624307913 100755 --- a/mindspore/lite/test/st/scripts/run_net_train.sh +++ b/mindspore/lite/test/st/scripts/run_net_train.sh @@ -121,6 +121,7 @@ function GenerateWeightQuantConfig() { function parse_line() { i=1 loss_name= + inputShapes= enable_fp16="false" virtual_batch="false" accuracy_limit=0.5 @@ -168,6 +169,10 @@ function parse_line() { "code_example") ret=1 ;; + "inputShapes") + i=$(($i+1)) + inputShapes=${line_array[i]} + ;; *) check=`echo "${line_array[i]}" | grep -E '^\-?[0-9]*\.?[0-9]+$'` if [ "${check}" != "" ] ; then @@ -227,6 +232,7 @@ function Run_x86() { --accuracyThreshold=${accuracy_limit} --inferenceFile=${inference_file} \ --exportFile=${export_file} \ --virtualBatch=${virtual_batch} \ + --inputShapes=${inputShapes} \ --lossName=${loss_name} " >> ${run_x86_log_file} ${run_valgrind} ./tools/benchmark_train/benchmark_train \ --modelFile=${model_file} \ @@ -236,6 +242,7 @@ function Run_x86() { --accuracyThreshold=${accuracy_limit} --inferenceFile=${inference_file} \ --exportFile=${export_file} \ --virtualBatch=${virtual_batch} \ + --inputShapes=${inputShapes} \ --lossName=${loss_name} >> "${run_x86_log_file}" if [ $? = 0 ]; then run_result='x86'${log_suffix}': '${model_name}''${suffix_print}' pass'; echo ${run_result} >> ${run_benchmark_train_result_file} @@ -362,6 +369,7 @@ function Run_arm() { --inferenceFile=${inference_file} \ --exportFile=${export_file} \ --virtualBatch=${virtual_batch} \ + --inputShapes=${inputShapes} \ --lossName=${loss_name} ENDM )