!14558 fix export mindir failure for fasterrcnn

From: @zhouneng2
Reviewed-by: @linqingke,@liangchenghui
Signed-off-by: @linqingke

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/AclProcess.cpp

@@ -284,19 +284,24 @@ int AclProcess::ModelInfer(std::map<double, double> *costTime_map) {
         heightScale = static_cast<float>(resizeOutData->height) / inputImg->height;
     }
 
-    float im_info[4];
-    im_info[0] = static_cast<float>(inputImg->height);
-    im_info[1] = static_cast<float>(inputImg->width);
-    im_info[2] = heightScale;
-    im_info[3] = widthScale;
+    aclFloat16 inputWidth = aclFloatToFloat16(static_cast<float>(inputImg->width));
+    aclFloat16 inputHeight = aclFloatToFloat16(static_cast<float>(inputImg->height));
+    aclFloat16 resizeWidthRatioFp16 = aclFloatToFloat16(widthScale);
+    aclFloat16 resizeHeightRatioFp16 = aclFloatToFloat16(heightScale);
+
+    aclFloat16 *im_info = reinterpret_cast<aclFloat16 *>(malloc(sizeof(aclFloat16) * 4));
+    im_info[0] = inputHeight;
+    im_info[1] = inputWidth;
+    im_info[2] = resizeHeightRatioFp16;
+    im_info[3] = resizeWidthRatioFp16;
     void *imInfo_dst = nullptr;
-    int ret = aclrtMalloc(&imInfo_dst, 16, ACL_MEM_MALLOC_NORMAL_ONLY);
+    int ret = aclrtMalloc(&imInfo_dst, 8, ACL_MEM_MALLOC_NORMAL_ONLY);
     if (ret != ACL_ERROR_NONE) {
         std::cout << "aclrtMalloc failed, ret = " << ret << std::endl;
         aclrtFree(imInfo_dst);
         return ret;
     }
-    ret = aclrtMemcpy(reinterpret_cast<uint8_t *>(imInfo_dst), 16, im_info, 16, ACL_MEMCPY_HOST_TO_DEVICE);
+    ret = aclrtMemcpy(reinterpret_cast<uint8_t *>(imInfo_dst), 8, im_info, 8, ACL_MEMCPY_HOST_TO_DEVICE);
     if (ret != ACL_ERROR_NONE) {
         std::cout << "aclrtMemcpy failed, ret = " << ret << std::endl;
         aclrtFree(imInfo_dst);

model_zoo/official/cv/faster_rcnn/export.py

@@ -17,6 +17,7 @@ import argparse
 import numpy as np
 
 import mindspore as ms
+import mindspore.common.dtype as mstype
 from mindspore import Tensor, load_checkpoint, load_param_into_net, export, context
 
 from src.FasterRcnn.faster_rcnn_r50 import FasterRcnn_Infer
@@ -46,6 +47,10 @@ if __name__ == '__main__':
 
     load_param_into_net(net, param_dict_new)
 
+    device_type = "Ascend" if context.get_context("device_target") == "Ascend" else "Others"
+    if device_type == "Ascend":
+        net.to_float(mstype.float16)
+
     img = Tensor(np.zeros([config.test_batch_size, 3, config.img_height, config.img_width]), ms.float32)
     img_metas = Tensor(np.random.uniform(0.0, 1.0, size=[config.test_batch_size, 4]), ms.float32)
 

model_zoo/official/cv/faster_rcnn/postprocess.py

@@ -45,7 +45,7 @@ def get_eval_result(ann_file):
         label_result_file = result_path + file_id + "_1.bin"
         mask_result_file = result_path + file_id + "_2.bin"
 
-        all_bbox = np.fromfile(bbox_result_file, dtype=np.float32).reshape(80000, 5)
+        all_bbox = np.fromfile(bbox_result_file, dtype=np.float16).reshape(80000, 5)
         all_label = np.fromfile(label_result_file, dtype=np.int32).reshape(80000, 1)
         all_mask = np.fromfile(mask_result_file, dtype=np.bool_).reshape(80000, 1)