From 8c3989d5689fb016738b38110bb4bc16074cbc25 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Tue, 15 Oct 2024 17:39:50 +0800 Subject: [PATCH] add requirement txt and uniform the excute way --- .../cv/classification/alexnet/ixrt/README.md | 6 +--- .../alexnet/ixrt/requirements.txt | 5 +++ .../classification/densenet121/ixrt/README.md | 9 ++--- .../{DENSENET_CONFIG => DENSENET121_CONFIG} | 0 .../densenet121/ixrt/inference.py | 4 +++ .../densenet121/ixrt/requirements.txt | 6 ++++ ....sh => infer_densenet121_fp16_accuracy.sh} | 0 ... => infer_densenet121_fp16_performance.sh} | 0 .../efficientnet_b0/ixrt/README.md | 9 ++--- .../ixrt/config/EFFICIENTNET_B0_CONFIG | 2 +- .../efficientnet_b0/ixrt/python/inference.py | 4 +++ .../efficientnet_b0/ixrt/requirements.txt | 7 ++++ .../infer_efficientnet_b0_fp16_accuracy.sh | 2 +- .../infer_efficientnet_b0_fp16_performance.sh | 6 +--- .../infer_efficientnet_b0_int8_accuracy.sh | 6 +--- .../infer_efficientnet_b0_int8_performance.sh | 6 +--- .../efficientnet_v2/ixrt/README.md | 31 +++++++--------- ...TNET_V2T_CONFIG => EFFICIENTNET_V2_CONFIG} | 4 +-- .../efficientnet_v2/ixrt/inference.py | 4 +++ .../efficientnet_v2/ixrt/requirements.txt | 8 +++++ ...=> infer_efficientnet_v2_fp16_accuracy.sh} | 0 ...infer_efficientnet_v2_fp16_performance.sh} | 0 ...=> infer_efficientnet_v2_int8_accuracy.sh} | 0 ...infer_efficientnet_v2_int8_performance.sh} | 0 .../classification/googlenet/ixrt/README.md | 5 +-- .../googlenet/ixrt/inference.py | 4 +++ .../googlenet/ixrt/requirements.txt | 4 +++ .../inception_v3/ixrt/README.md | 10 ++---- .../ixrt/config/INCEPTION_V3_CONFIG | 2 +- .../inception_v3/ixrt/inference.py | 4 +++ .../inception_v3/ixrt/requirements.txt | 7 ++++ .../mobilenet_v2/ixrt/README.md | 25 +++++++++---- .../mobilenet_v2/ixrt/python/export_onnx.py | 5 ++- .../mobilenet_v2/ixrt/requirements.txt | 5 +++ .../script/infer_mobilenetv2_fp16_accuracy.sh | 28 ++++++--------- .../infer_mobilenetv2_fp16_performance.sh | 28 ++++++--------- .../script/infer_mobilenetv2_int8_accuracy.sh | 30 ++++++---------- .../infer_mobilenetv2_int8_performance.sh | 30 ++++++---------- .../mobilenet_v3/ixrt/README.md | 13 +++---- ...MOBILENETV3_CONFIG => MOBILENET_V3_CONFIG} | 2 +- .../mobilenet_v3/ixrt/inference.py | 4 +++ .../mobilenet_v3/ixrt/requirements.txt | 4 +++ ...sh => infer_mobilenet_v3_fp16_accuracy.sh} | 0 ...=> infer_mobilenet_v3_fp16_performance.sh} | 0 .../classification/res2net50/ixrt/README.md | 9 +++-- .../res2net50/ixrt/export_onnx.py | 14 ++------ .../res2net50/ixrt/inference.py | 4 +++ .../res2net50/ixrt/requirements.txt | 4 +++ .../cv/classification/resnet18/ixrt/README.md | 9 +++-- .../resnet18/ixrt/export_onnx.py | 4 ++- .../classification/resnet18/ixrt/inference.py | 4 +++ .../resnet18/ixrt/requirements.txt | 4 +++ .../shufflenet_v1/ixrt/README.md | 12 +++---- .../shufflenet_v1/ixrt/inference.py | 4 +++ .../shufflenet_v1/ixrt/requirements.txt | 7 ++++ .../ixrt/README.md | 10 ++---- .../ixrt/build_engine.py | 0 .../ixrt/build_i8_engine.py | 0 .../ixrt/calibration_dataset.py | 0 .../ixrt/common.py | 0 .../ixrt/config/SQUEEZENET_V11_CONFIG | 2 +- .../ixrt/export_onnx.py | 0 .../ixrt/inference.py | 4 +++ .../ixrt/modify_batchsize.py | 0 .../ixrt/quant.py | 0 .../ixrt/refine_model.py | 0 .../squeezenet_v11/ixrt/requirements.txt | 7 ++++ .../infer_squeezenet_v11_fp16_accuracy.sh | 0 .../infer_squeezenet_v11_fp16_performance.sh | 0 .../infer_squeezenet_v11_int8_accuracy.sh | 0 .../infer_squeezenet_v11_int8_performance.sh | 0 .../ixrt/simplify_model.py | 0 models/cv/classification/vgg16/ixrt/README.md | 8 ++--- .../classification/vgg16/ixrt/export_onnx.py | 4 ++- .../cv/classification/vgg16/ixrt/inference.py | 4 +++ .../vgg16/ixrt/requirements.txt | 3 ++ models/cv/detection/yolov8/igie/README.md | 2 +- models/cv/detection/yolov8/ixrt/README.md | 36 +++++++++---------- .../cv/detection/yolov8/ixrt/requirements.txt | 6 ++++ ...uracy.sh => infer_yolov8_fp16_accuracy.sh} | 14 ++++---- ...ce.sh => infer_yolov8_fp16_performance.sh} | 14 ++++---- ...uracy.sh => infer_yolov8_int8_accuracy.sh} | 18 +++++----- ...ce.sh => infer_yolov8_int8_performance.sh} | 18 +++++----- 83 files changed, 296 insertions(+), 258 deletions(-) create mode 100644 models/cv/classification/alexnet/ixrt/requirements.txt rename models/cv/classification/densenet121/ixrt/config/{DENSENET_CONFIG => DENSENET121_CONFIG} (100%) create mode 100644 models/cv/classification/densenet121/ixrt/requirements.txt rename models/cv/classification/densenet121/ixrt/scripts/{infer_densenet_fp16_accuracy.sh => infer_densenet121_fp16_accuracy.sh} (100%) rename models/cv/classification/densenet121/ixrt/scripts/{infer_densenet_fp16_performance.sh => infer_densenet121_fp16_performance.sh} (100%) create mode 100644 models/cv/classification/efficientnet_b0/ixrt/requirements.txt rename models/cv/classification/efficientnet_v2/ixrt/config/{EFFICIENTNET_V2T_CONFIG => EFFICIENTNET_V2_CONFIG} (95%) create mode 100644 models/cv/classification/efficientnet_v2/ixrt/requirements.txt rename models/cv/classification/efficientnet_v2/ixrt/scripts/{infer_efficientnet_fp16_accuracy.sh => infer_efficientnet_v2_fp16_accuracy.sh} (100%) mode change 100755 => 100644 rename models/cv/classification/efficientnet_v2/ixrt/scripts/{infer_efficientnet_fp16_performance.sh => infer_efficientnet_v2_fp16_performance.sh} (100%) mode change 100755 => 100644 rename models/cv/classification/efficientnet_v2/ixrt/scripts/{infer_efficientnet_int8_accuracy.sh => infer_efficientnet_v2_int8_accuracy.sh} (100%) mode change 100755 => 100644 rename models/cv/classification/efficientnet_v2/ixrt/scripts/{infer_efficientnet_int8_performance.sh => infer_efficientnet_v2_int8_performance.sh} (100%) mode change 100755 => 100644 create mode 100644 models/cv/classification/googlenet/ixrt/requirements.txt create mode 100644 models/cv/classification/inception_v3/ixrt/requirements.txt create mode 100644 models/cv/classification/mobilenet_v2/ixrt/requirements.txt rename models/cv/classification/mobilenet_v2/ixrt/{python => }/script/infer_mobilenetv2_fp16_accuracy.sh (80%) rename models/cv/classification/mobilenet_v2/ixrt/{python => }/script/infer_mobilenetv2_fp16_performance.sh (80%) rename models/cv/classification/mobilenet_v2/ixrt/{python => }/script/infer_mobilenetv2_int8_accuracy.sh (82%) rename models/cv/classification/mobilenet_v2/ixrt/{python => }/script/infer_mobilenetv2_int8_performance.sh (82%) rename models/cv/classification/mobilenet_v3/ixrt/config/{MOBILENETV3_CONFIG => MOBILENET_V3_CONFIG} (97%) create mode 100644 models/cv/classification/mobilenet_v3/ixrt/requirements.txt rename models/cv/classification/mobilenet_v3/ixrt/scripts/{infer_mobilenetv3_fp16_accuracy.sh => infer_mobilenet_v3_fp16_accuracy.sh} (100%) rename models/cv/classification/mobilenet_v3/ixrt/scripts/{infer_mobilenetv3_fp16_performance.sh => infer_mobilenet_v3_fp16_performance.sh} (100%) create mode 100644 models/cv/classification/res2net50/ixrt/requirements.txt create mode 100644 models/cv/classification/resnet18/ixrt/requirements.txt create mode 100644 models/cv/classification/shufflenet_v1/ixrt/requirements.txt rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/README.md (87%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/build_engine.py (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/build_i8_engine.py (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/calibration_dataset.py (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/common.py (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/config/SQUEEZENET_V11_CONFIG (95%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/export_onnx.py (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/inference.py (96%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/modify_batchsize.py (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/quant.py (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/refine_model.py (100%) create mode 100644 models/cv/classification/squeezenet_v11/ixrt/requirements.txt rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/scripts/infer_squeezenet_v11_fp16_accuracy.sh (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/scripts/infer_squeezenet_v11_fp16_performance.sh (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/scripts/infer_squeezenet_v11_int8_accuracy.sh (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/scripts/infer_squeezenet_v11_int8_performance.sh (100%) rename models/cv/classification/{squeezenet_1.1 => squeezenet_v11}/ixrt/simplify_model.py (100%) create mode 100644 models/cv/classification/vgg16/ixrt/requirements.txt create mode 100644 models/cv/detection/yolov8/ixrt/requirements.txt rename models/cv/detection/yolov8/ixrt/scripts/{infer_yolov8n_fp16_accuracy.sh => infer_yolov8_fp16_accuracy.sh} (88%) rename models/cv/detection/yolov8/ixrt/scripts/{infer_yolov8n_fp16_performance.sh => infer_yolov8_fp16_performance.sh} (88%) rename models/cv/detection/yolov8/ixrt/scripts/{infer_yolov8n_int8_accuracy.sh => infer_yolov8_int8_accuracy.sh} (90%) rename models/cv/detection/yolov8/ixrt/scripts/{infer_yolov8n_int8_performance.sh => infer_yolov8_int8_performance.sh} (89%) diff --git a/models/cv/classification/alexnet/ixrt/README.md b/models/cv/classification/alexnet/ixrt/README.md index 4a25a911..65fa53ef 100644 --- a/models/cv/classification/alexnet/ixrt/README.md +++ b/models/cv/classification/alexnet/ixrt/README.md @@ -15,11 +15,7 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate -pip3 install pycuda +pip3 install -r requirements.txt ``` ### Download diff --git a/models/cv/classification/alexnet/ixrt/requirements.txt b/models/cv/classification/alexnet/ixrt/requirements.txt new file mode 100644 index 00000000..bc645b22 --- /dev/null +++ b/models/cv/classification/alexnet/ixrt/requirements.txt @@ -0,0 +1,5 @@ +tqdm +onnx +onnxsim +tabulate +pycuda \ No newline at end of file diff --git a/models/cv/classification/densenet121/ixrt/README.md b/models/cv/classification/densenet121/ixrt/README.md index 9b5c2078..f506c085 100644 --- a/models/cv/classification/densenet121/ixrt/README.md +++ b/models/cv/classification/densenet121/ixrt/README.md @@ -15,12 +15,7 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate -pip3 install ppq -pip3 install pycuda +pip3 install -r requirements.txt ``` ### Download @@ -40,7 +35,7 @@ python3 export_onnx.py --output_model checkpoints/densenet121.onnx export DATASETS_DIR=/path/to/imagenet_val/ export CHECKPOINTS_DIR=./checkpoints export RUN_DIR=./ -export CONFIG_DIR=config/DENSENET_CONFIG +export CONFIG_DIR=config/DENSENET121_CONFIG ``` ### FP16 diff --git a/models/cv/classification/densenet121/ixrt/config/DENSENET_CONFIG b/models/cv/classification/densenet121/ixrt/config/DENSENET121_CONFIG similarity index 100% rename from models/cv/classification/densenet121/ixrt/config/DENSENET_CONFIG rename to models/cv/classification/densenet121/ixrt/config/DENSENET121_CONFIG diff --git a/models/cv/classification/densenet121/ixrt/inference.py b/models/cv/classification/densenet121/ixrt/inference.py index 2c9dcb3f..50aafd4f 100644 --- a/models/cv/classification/densenet121/ixrt/inference.py +++ b/models/cv/classification/densenet121/ixrt/inference.py @@ -83,6 +83,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -104,7 +105,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/densenet121/ixrt/requirements.txt b/models/cv/classification/densenet121/ixrt/requirements.txt new file mode 100644 index 00000000..01ec4f11 --- /dev/null +++ b/models/cv/classification/densenet121/ixrt/requirements.txt @@ -0,0 +1,6 @@ +tqdm +onnx +onnxsim +tabulate +ppq +pycuda \ No newline at end of file diff --git a/models/cv/classification/densenet121/ixrt/scripts/infer_densenet_fp16_accuracy.sh b/models/cv/classification/densenet121/ixrt/scripts/infer_densenet121_fp16_accuracy.sh similarity index 100% rename from models/cv/classification/densenet121/ixrt/scripts/infer_densenet_fp16_accuracy.sh rename to models/cv/classification/densenet121/ixrt/scripts/infer_densenet121_fp16_accuracy.sh diff --git a/models/cv/classification/densenet121/ixrt/scripts/infer_densenet_fp16_performance.sh b/models/cv/classification/densenet121/ixrt/scripts/infer_densenet121_fp16_performance.sh similarity index 100% rename from models/cv/classification/densenet121/ixrt/scripts/infer_densenet_fp16_performance.sh rename to models/cv/classification/densenet121/ixrt/scripts/infer_densenet121_fp16_performance.sh diff --git a/models/cv/classification/efficientnet_b0/ixrt/README.md b/models/cv/classification/efficientnet_b0/ixrt/README.md index bf57f509..e7f3087b 100644 --- a/models/cv/classification/efficientnet_b0/ixrt/README.md +++ b/models/cv/classification/efficientnet_b0/ixrt/README.md @@ -15,12 +15,7 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate -pip3 install ppq==0.6.6 -pip install protobuf==3.20.3 pycuda +pip3 install -r requirements.txt ``` ### Download @@ -32,7 +27,7 @@ Dataset: to download the validation dat ### Model Conversion ```bash -python3 python/export_onnx.py --origin_model /path/to/efficientnet_b0_rwightman-3dd342df.pth --output_model efficientnet-b0.onnx +python3 python/export_onnx.py --origin_model /path/to/efficientnet_b0_rwightman-3dd342df.pth --output_model efficientnet_b0.onnx ``` ## Inference diff --git a/models/cv/classification/efficientnet_b0/ixrt/config/EFFICIENTNET_B0_CONFIG b/models/cv/classification/efficientnet_b0/ixrt/config/EFFICIENTNET_B0_CONFIG index f9a0976e..f566df01 100644 --- a/models/cv/classification/efficientnet_b0/ixrt/config/EFFICIENTNET_B0_CONFIG +++ b/models/cv/classification/efficientnet_b0/ixrt/config/EFFICIENTNET_B0_CONFIG @@ -18,7 +18,7 @@ # ORIGINE_MODEL : 原始onnx文件名称 IMGSIZE=224 MODEL_NAME=EfficientNet_b0 -ORIGINE_MODEL=efficientnet-b0.onnx +ORIGINE_MODEL=efficientnet_b0.onnx # QUANT CONFIG (仅PRECISION为int8时生效) # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema] diff --git a/models/cv/classification/efficientnet_b0/ixrt/python/inference.py b/models/cv/classification/efficientnet_b0/ixrt/python/inference.py index 414546b2..f1155702 100644 --- a/models/cv/classification/efficientnet_b0/ixrt/python/inference.py +++ b/models/cv/classification/efficientnet_b0/ixrt/python/inference.py @@ -85,6 +85,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -106,7 +107,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/efficientnet_b0/ixrt/requirements.txt b/models/cv/classification/efficientnet_b0/ixrt/requirements.txt new file mode 100644 index 00000000..46a30ba2 --- /dev/null +++ b/models/cv/classification/efficientnet_b0/ixrt/requirements.txt @@ -0,0 +1,7 @@ +tqdm +onnx +onnxsim +tabulate +ppq==0.6.6 +protobuf==3.20.3 +pycuda \ No newline at end of file diff --git a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_accuracy.sh b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_accuracy.sh index a8ca6d11..f184e30d 100644 --- a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_accuracy.sh +++ b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_accuracy.sh @@ -14,7 +14,7 @@ # License for the specific language governing permissions and limitations # under the License. batchsize=32 -model_path="efficientnet-b0" +model_path="efficientnet_b0" # model_path="resnet18" datasets_path=${DATASETS_DIR} diff --git a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_performance.sh b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_performance.sh index ca523b2f..458d9136 100644 --- a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_performance.sh +++ b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_performance.sh @@ -14,14 +14,10 @@ # License for the specific language governing permissions and limitations # under the License. batchsize=32 -model_path="efficientnet-b0" +model_path="efficientnet_b0" # model_path="resnet18" datasets_path=${DATASETS_DIR} -# create onnx -python3 python/export_onnx.py \ - --output_model ${model_path}.onnx - # change batchsize python3 python/modify_batchsize.py \ --batch_size ${batchsize} \ diff --git a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_accuracy.sh b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_accuracy.sh index 5f1c4827..82517f70 100644 --- a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_accuracy.sh +++ b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_accuracy.sh @@ -14,14 +14,10 @@ # License for the specific language governing permissions and limitations # under the License. batchsize=32 -model_path="efficientnet-b0" +model_path="efficientnet_b0" # model_path="resnet18" datasets_path=${DATASETS_DIR} -# create onnx -python3 python/export_onnx.py \ - --output_model ${model_path}.onnx - # change batchsize python3 python/modify_batchsize.py \ --batch_size ${batchsize} \ diff --git a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_performance.sh b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_performance.sh index 9c1e159f..4a40c030 100644 --- a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_performance.sh +++ b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_performance.sh @@ -14,14 +14,10 @@ # License for the specific language governing permissions and limitations # under the License. batchsize=32 -model_path="efficientnet-b0" +model_path="efficientnet_b0" # model_path="resnet18" datasets_path=${DATASETS_DIR} -# create onnx -python3 python/export_onnx.py \ - --output_model ${model_path}.onnx - # change batchsize python3 python/modify_batchsize.py \ --batch_size ${batchsize} \ diff --git a/models/cv/classification/efficientnet_v2/ixrt/README.md b/models/cv/classification/efficientnet_v2/ixrt/README.md index 23c83cf5..ee919749 100755 --- a/models/cv/classification/efficientnet_v2/ixrt/README.md +++ b/models/cv/classification/efficientnet_v2/ixrt/README.md @@ -15,14 +15,7 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate -pip3 install timm -pip3 install ppq -pip3 install pycuda -pip3 install protobuf==3.20.0 +pip3 install -r requirements.txt ``` ### Download @@ -35,15 +28,15 @@ Dataset: to download the validation dat ```bash mkdir checkpoints -git clone https://github.com/huggingface/pytorch-image-models.git && git checkout -cp /Path/to/ixrt/export_onnx.py pytorch-image-models/timm/models -cd pytorch-image-models/timm/models -rm _builder.py -mv /Path/ixrt/_builder.py pytorch-image-models/timm/models +git clone https://github.com/huggingface/pytorch-image-models.git +cp ./export_onnx.py pytorch-image-models/timm/models +rm pytorch-image-models/timm/models/_builder.py +mv ./_builder.py pytorch-image-models/timm/models cd pytorch-image-models/timm mkdir -p /root/.cache/torch/hub/checkpoints/ wget -P /root/.cache/torch/hub/checkpoints/ https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnetv2_t_agc-3620981a.pth -python3 -m models.export_onnx --output_model ../../checkpoints/efficientnet.onnx +python3 -m models.export_onnx --output_model ../../checkpoints/efficientnet_v2.onnx +cd ../../ ``` ## Inference @@ -53,7 +46,7 @@ export PROJ_DIR=/Path/to/efficientnet_v2/ixrt export DATASETS_DIR=/path/to/imagenet_val/ export CHECKPOINTS_DIR=./checkpoints export RUN_DIR=/Path/to/efficientnet_v2/ixrt -export CONFIG_DIR=/Path/to/config/EFFICIENTNET_V2T_CONFIG +export CONFIG_DIR=/Path/to/config/EFFICIENTNET_V2_CONFIG export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python ``` @@ -61,18 +54,18 @@ export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python ```bash # Accuracy -bash scripts/infer_efficientnet_fp16_accuracy.sh +bash scripts/infer_efficientnet_v2_fp16_accuracy.sh # Performance -bash scripts/infer_efficientnet_fp16_performance.sh +bash scripts/infer_efficientnet_v2_fp16_performance.sh ``` ### INT8 ```bash # Accuracy -bash scripts/infer_efficientnet_int8_accuracy.sh +bash scripts/infer_efficientnet_v2_int8_accuracy.sh # Performance -bash scripts/infer_efficientnet_int8_performance.sh +bash scripts/infer_efficientnet_v2_int8_performance.sh ``` ## Results diff --git a/models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2T_CONFIG b/models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2_CONFIG similarity index 95% rename from models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2T_CONFIG rename to models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2_CONFIG index b9e40159..6979f31d 100644 --- a/models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2T_CONFIG +++ b/models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2_CONFIG @@ -17,8 +17,8 @@ # MODEL_NAME : 生成onnx/engine的basename # ORIGINE_MODEL : 原始onnx文件名称 IMGSIZE=288 -MODEL_NAME=EfficientNetv2_t -ORIGINE_MODEL=efficientnet.onnx +MODEL_NAME=efficientnet_v2 +ORIGINE_MODEL=efficientnet_v2.onnx # QUANT CONFIG (仅PRECISION为int8时生效) # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema] diff --git a/models/cv/classification/efficientnet_v2/ixrt/inference.py b/models/cv/classification/efficientnet_v2/ixrt/inference.py index 62ec18b3..fcca27a3 100644 --- a/models/cv/classification/efficientnet_v2/ixrt/inference.py +++ b/models/cv/classification/efficientnet_v2/ixrt/inference.py @@ -85,6 +85,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -106,7 +107,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/efficientnet_v2/ixrt/requirements.txt b/models/cv/classification/efficientnet_v2/ixrt/requirements.txt new file mode 100644 index 00000000..09e8dab9 --- /dev/null +++ b/models/cv/classification/efficientnet_v2/ixrt/requirements.txt @@ -0,0 +1,8 @@ +tqdm +onnx +onnxsim +tabulate +timm==1.0.10 +ppq +pycuda +protobuf==3.20.0 \ No newline at end of file diff --git a/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_fp16_accuracy.sh b/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_fp16_accuracy.sh old mode 100755 new mode 100644 similarity index 100% rename from models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_fp16_accuracy.sh rename to models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_fp16_accuracy.sh diff --git a/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_fp16_performance.sh b/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_fp16_performance.sh old mode 100755 new mode 100644 similarity index 100% rename from models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_fp16_performance.sh rename to models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_fp16_performance.sh diff --git a/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_int8_accuracy.sh b/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_int8_accuracy.sh old mode 100755 new mode 100644 similarity index 100% rename from models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_int8_accuracy.sh rename to models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_int8_accuracy.sh diff --git a/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_int8_performance.sh b/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_int8_performance.sh old mode 100755 new mode 100644 similarity index 100% rename from models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_int8_performance.sh rename to models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_int8_performance.sh diff --git a/models/cv/classification/googlenet/ixrt/README.md b/models/cv/classification/googlenet/ixrt/README.md index 001319b6..fa96b475 100644 --- a/models/cv/classification/googlenet/ixrt/README.md +++ b/models/cv/classification/googlenet/ixrt/README.md @@ -15,10 +15,7 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate +pip3 install -r requirements.txt ``` ### Download diff --git a/models/cv/classification/googlenet/ixrt/inference.py b/models/cv/classification/googlenet/ixrt/inference.py index 2c9dcb3f..50aafd4f 100644 --- a/models/cv/classification/googlenet/ixrt/inference.py +++ b/models/cv/classification/googlenet/ixrt/inference.py @@ -83,6 +83,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -104,7 +105,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/googlenet/ixrt/requirements.txt b/models/cv/classification/googlenet/ixrt/requirements.txt new file mode 100644 index 00000000..e1eda59c --- /dev/null +++ b/models/cv/classification/googlenet/ixrt/requirements.txt @@ -0,0 +1,4 @@ +tqdm +onnx +onnxsim +tabulate \ No newline at end of file diff --git a/models/cv/classification/inception_v3/ixrt/README.md b/models/cv/classification/inception_v3/ixrt/README.md index 523fa268..4fbbe94f 100755 --- a/models/cv/classification/inception_v3/ixrt/README.md +++ b/models/cv/classification/inception_v3/ixrt/README.md @@ -15,13 +15,7 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install pycuda -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate -pip3 install ppq -pip3 install protobuf==3.20.0 +pip3 install -r requirements.txt ``` ### Download @@ -35,7 +29,7 @@ Dataset: to download the validation dat ```bash mkdir checkpoints -python3 export.py --weight inception_v3_google-0cc3c7bd.pth --output checkpoints/inception-v3.onnx +python3 export.py --weight inception_v3_google-0cc3c7bd.pth --output checkpoints/inception_v3.onnx ``` ## Inference diff --git a/models/cv/classification/inception_v3/ixrt/config/INCEPTION_V3_CONFIG b/models/cv/classification/inception_v3/ixrt/config/INCEPTION_V3_CONFIG index f5223eaf..041b0910 100644 --- a/models/cv/classification/inception_v3/ixrt/config/INCEPTION_V3_CONFIG +++ b/models/cv/classification/inception_v3/ixrt/config/INCEPTION_V3_CONFIG @@ -18,7 +18,7 @@ # ORIGINE_MODEL : 原始onnx文件名称 IMGSIZE=224 MODEL_NAME=Inception_v3 -ORIGINE_MODEL=inception-v3.onnx +ORIGINE_MODEL=inception_v3.onnx # QUANT CONFIG (仅PRECISION为int8时生效) # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema] diff --git a/models/cv/classification/inception_v3/ixrt/inference.py b/models/cv/classification/inception_v3/ixrt/inference.py index 62ec18b3..fcca27a3 100644 --- a/models/cv/classification/inception_v3/ixrt/inference.py +++ b/models/cv/classification/inception_v3/ixrt/inference.py @@ -85,6 +85,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -106,7 +107,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/inception_v3/ixrt/requirements.txt b/models/cv/classification/inception_v3/ixrt/requirements.txt new file mode 100644 index 00000000..bb2683dd --- /dev/null +++ b/models/cv/classification/inception_v3/ixrt/requirements.txt @@ -0,0 +1,7 @@ +pycuda +tqdm +onnx +onnxsim +tabulate +ppq +protobuf==3.20.0 \ No newline at end of file diff --git a/models/cv/classification/mobilenet_v2/ixrt/README.md b/models/cv/classification/mobilenet_v2/ixrt/README.md index d3a375f8..65e27ec4 100644 --- a/models/cv/classification/mobilenet_v2/ixrt/README.md +++ b/models/cv/classification/mobilenet_v2/ixrt/README.md @@ -9,23 +9,34 @@ The MobileNetV2 architecture is based on an inverted residual structure where th ### Install ```bash -pip3 install tqdm -pip3 install onnxsim -pip3 install opencv-python -pip3 install ppq -pip3 install protobuf==3.20.0 +pip3 install -r requirements.txt ``` ### Download -Download the [imagenet](https://www.image-net.org/download.php) validation dataset, and place in `${PROJ_ROOT}/data/datasets`; +Pretrained model: + +Download the [imagenet](https://www.image-net.org/download.php) to download the validation dataset. + +### Model Conversion + +```bash +mkdir checkpoints +python3 python/export_onnx.py --origin_model /path/to/mobilenet_v2-b0353104 --output_model checkpoints/mobilenet_v2.onnx +``` ## Inference +```bash +export PROJ_DIR=./ +export DATASETS_DIR=/path/to/imagenet_val/ +export CHECKPOINTS_DIR=./checkpoints +export RUN_DIR=./ +``` + ### FP16 ```bash -cd python/ # Test ACC bash script/infer_mobilenetv2_fp16_accuracy.sh # Test FPS diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/export_onnx.py b/models/cv/classification/mobilenet_v2/ixrt/python/export_onnx.py index 8351ffc8..4881a4c1 100644 --- a/models/cv/classification/mobilenet_v2/ixrt/python/export_onnx.py +++ b/models/cv/classification/mobilenet_v2/ixrt/python/export_onnx.py @@ -20,13 +20,15 @@ import argparse def parse_args(): parser = argparse.ArgumentParser() + parser.add_argument("--origin_model", type=str) parser.add_argument("--output_model", type=str) args = parser.parse_args() return args args = parse_args() -model = models.mobilenet_v2(pretrained=True) +model = models.mobilenet_v2() +model.load_state_dict(torch.load(args.origin_model)) model.cuda() model.eval() inputx = torch.randn(1, 3, 224, 224, device='cuda') @@ -42,3 +44,4 @@ torch.onnx.export(model, input_names = ['input'], output_names = ['output'],) print(f"Convert onnx model in {export_onnx_file}") +exit() diff --git a/models/cv/classification/mobilenet_v2/ixrt/requirements.txt b/models/cv/classification/mobilenet_v2/ixrt/requirements.txt new file mode 100644 index 00000000..a6b325a7 --- /dev/null +++ b/models/cv/classification/mobilenet_v2/ixrt/requirements.txt @@ -0,0 +1,5 @@ +tqdm +onnxsim +opencv-python +ppq +protobuf==3.20.0 \ No newline at end of file diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_accuracy.sh b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_accuracy.sh similarity index 80% rename from models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_accuracy.sh rename to models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_accuracy.sh index 93c3cda4..f3e4828d 100644 --- a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_accuracy.sh +++ b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_accuracy.sh @@ -44,18 +44,18 @@ do esac done -RUN_DIR=$(cd $(dirname $0); cd ../; pwd) -PROJ_DIR=$(cd $(dirname $0); cd ../../../../../../../; pwd) -DATASETS_DIR="${PROJ_DIR}/data/datasets/imagenet_val" -CHECKPOINTS_DIR="${PROJ_DIR}/data/checkpoints/mobilenetv2" +RUN_DIR=${RUN_DIR} +PROJ_DIR=${PROJ_DIR} +DATASETS_DIR=${DATASETS_DIR} +CHECKPOINTS_DIR=${CHECKPOINTS_DIR} if [ ! -d $CHECKPOINTS_DIR ]; then mkdir -p $CHECKPOINTS_DIR fi -MODEL_NAME="mobilenetv2" -ORIGINE_MODEL="${CHECKPOINTS_DIR}/raw_mobilenetv2.onnx" +MODEL_NAME="mobilenet_v2" +ORIGINE_MODEL="${CHECKPOINTS_DIR}/mobilenet_v2.onnx" echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR} echo DATASETS_DIR : ${DATASETS_DIR} @@ -69,14 +69,6 @@ step=0 # Export Onnx Model let step++ echo; -echo [STEP ${step}] : Export Onnx Model -if [ -f ${ORIGINE_MODEL} ];then - echo " "Onnx Model, ${ORIGINE_MODEL} has been existed -else - python3 ${RUN_DIR}/export_onnx.py \ - --output_model $ORIGINE_MODEL - echo " "Generate ${ORIGINE_MODEL} -fi SIM_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_sim.onnx # Simplify Model @@ -86,7 +78,7 @@ echo [STEP ${step}] : Simplify Model if [ -f ${SIM_MODEL} ];then echo " "Simplify Model, ${SIM_MODEL} has been existed else - python3 ${RUN_DIR}/simplify_model.py \ + python3 ${RUN_DIR}python/simplify_model.py \ --origin_model $ORIGINE_MODEL \ --output_model ${SIM_MODEL} echo " "Generate ${SIM_MODEL} @@ -100,7 +92,7 @@ FINAL_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_${BSZ}.onnx if [ -f $FINAL_MODEL ];then echo " "Change Batchsize Skip, $FINAL_MODEL has been existed else - python3 ${RUN_DIR}/modify_batchsize.py \ + python3 ${RUN_DIR}python/modify_batchsize.py \ --batch_size ${BSZ} \ --origin_model ${SIM_MODEL} \ --output_model ${FINAL_MODEL} @@ -115,7 +107,7 @@ ENGINE_FILE=${CHECKPOINTS_DIR}/${MODEL_NAME}_${PRECISION}_bs${BSZ}.engine if [ -f $ENGINE_FILE ];then echo " "Build Engine Skip, $ENGINE_FILE has been existed else - python3 ${RUN_DIR}/build_engine.py \ + python3 ${RUN_DIR}python/build_engine.py \ --precision ${PRECISION} \ --model ${FINAL_MODEL} \ --engine ${ENGINE_FILE} @@ -126,7 +118,7 @@ fi let step++ echo; echo [STEP ${step}] : Inference -python3 ${RUN_DIR}/inference.py \ +python3 ${RUN_DIR}python/inference.py \ --engine_file=${ENGINE_FILE} \ --datasets_dir=${DATASETS_DIR} \ --imgsz=${IMGSIZE} \ diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_performance.sh b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_performance.sh similarity index 80% rename from models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_performance.sh rename to models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_performance.sh index 1042fb91..1057dadb 100644 --- a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_performance.sh +++ b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_performance.sh @@ -44,18 +44,18 @@ do esac done -RUN_DIR=$(cd $(dirname $0); cd ../; pwd) -PROJ_DIR=$(cd $(dirname $0); cd ../../../../../../../; pwd) -DATASETS_DIR="${PROJ_DIR}/data/datasets/imagenet_val" -CHECKPOINTS_DIR="${PROJ_DIR}/data/checkpoints/mobilenetv2" +RUN_DIR=${RUN_DIR} +PROJ_DIR=${PROJ_DIR} +DATASETS_DIR=${DATASETS_DIR} +CHECKPOINTS_DIR=${CHECKPOINTS_DIR} if [ ! -d $CHECKPOINTS_DIR ]; then mkdir -p $CHECKPOINTS_DIR fi -MODEL_NAME="mobilenetv2" -ORIGINE_MODEL="${CHECKPOINTS_DIR}/raw_mobilenetv2.onnx" +MODEL_NAME="mobilenet_v2" +ORIGINE_MODEL="${CHECKPOINTS_DIR}/mobilenet_v2.onnx" echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR} echo DATASETS_DIR : ${DATASETS_DIR} @@ -69,14 +69,6 @@ step=0 # Export Onnx Model let step++ echo; -echo [STEP ${step}] : Export Onnx Model -if [ -f ${ORIGINE_MODEL} ];then - echo " "Onnx Model, ${ORIGINE_MODEL} has been existed -else - python3 ${RUN_DIR}/export_onnx.py \ - --output_model $ORIGINE_MODEL - echo " "Generate ${ORIGINE_MODEL} -fi SIM_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_sim.onnx # Simplify Model @@ -86,7 +78,7 @@ echo [STEP ${step}] : Simplify Model if [ -f ${SIM_MODEL} ];then echo " "Simplify Model, ${SIM_MODEL} has been existed else - python3 ${RUN_DIR}/simplify_model.py \ + python3 ${RUN_DIR}python/simplify_model.py \ --origin_model $ORIGINE_MODEL \ --output_model ${SIM_MODEL} echo " "Generate ${SIM_MODEL} @@ -100,7 +92,7 @@ FINAL_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_${BSZ}.onnx if [ -f $FINAL_MODEL ];then echo " "Change Batchsize Skip, $FINAL_MODEL has been existed else - python3 ${RUN_DIR}/modify_batchsize.py \ + python3 ${RUN_DIR}python/modify_batchsize.py \ --batch_size ${BSZ} \ --origin_model ${SIM_MODEL} \ --output_model ${FINAL_MODEL} @@ -115,7 +107,7 @@ ENGINE_FILE=${CHECKPOINTS_DIR}/${MODEL_NAME}_${PRECISION}_bs${BSZ}.engine if [ -f $ENGINE_FILE ];then echo " "Build Engine Skip, $ENGINE_FILE has been existed else - python3 ${RUN_DIR}/build_engine.py \ + python3 ${RUN_DIR}python/build_engine.py \ --precision ${PRECISION} \ --model ${FINAL_MODEL} \ --engine ${ENGINE_FILE} @@ -126,7 +118,7 @@ fi let step++ echo; echo [STEP ${step}] : Inference -python3 ${RUN_DIR}/inference.py \ +python3 ${RUN_DIR}python/inference.py \ --engine_file=${ENGINE_FILE} \ --datasets_dir=${DATASETS_DIR} \ --imgsz=${IMGSIZE} \ diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_accuracy.sh b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_accuracy.sh similarity index 82% rename from models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_accuracy.sh rename to models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_accuracy.sh index 7c32c789..95653d9f 100644 --- a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_accuracy.sh +++ b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_accuracy.sh @@ -44,18 +44,18 @@ do esac done -RUN_DIR=$(cd $(dirname $0); cd ../; pwd) -PROJ_DIR=$(cd $(dirname $0); cd ../../../../../../../; pwd) -DATASETS_DIR="${PROJ_DIR}/data/datasets/imagenet_val" -CHECKPOINTS_DIR="${PROJ_DIR}/data/checkpoints/mobilenetv2" +RUN_DIR=${RUN_DIR} +PROJ_DIR=${PROJ_DIR} +DATASETS_DIR=${DATASETS_DIR} +CHECKPOINTS_DIR=${CHECKPOINTS_DIR} if [ ! -d $CHECKPOINTS_DIR ]; then mkdir -p $CHECKPOINTS_DIR fi -MODEL_NAME="mobilenetv2" -ORIGINE_MODEL="${CHECKPOINTS_DIR}/raw_mobilenetv2.onnx" +MODEL_NAME="mobilenet_v2" +ORIGINE_MODEL="${CHECKPOINTS_DIR}/mobilenet_v2.onnx" echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR} echo DATASETS_DIR : ${DATASETS_DIR} @@ -69,14 +69,6 @@ step=0 # Export Onnx Model let step++ echo; -echo [STEP ${step}] : Export Onnx Model -if [ -f ${ORIGINE_MODEL} ];then - echo " "Onnx Model, ${ORIGINE_MODEL} has been existed -else - python3 ${RUN_DIR}/export_onnx.py \ - --output_model $ORIGINE_MODEL - echo " "Generate ${ORIGINE_MODEL} -fi SIM_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_sim.onnx # Simplify Model @@ -86,7 +78,7 @@ echo [STEP ${step}] : Simplify Model if [ -f ${SIM_MODEL} ];then echo " "Simplify Model, ${SIM_MODEL} has been existed else - python3 ${RUN_DIR}/simplify_model.py \ + python3 ${RUN_DIR}python/simplify_model.py \ --origin_model $ORIGINE_MODEL \ --output_model ${SIM_MODEL} echo " "Generate ${SIM_MODEL} @@ -100,7 +92,7 @@ FINAL_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_${BSZ}.onnx if [ -f $FINAL_MODEL ];then echo " "Change Batchsize Skip, $FINAL_MODEL has been existed else - python3 ${RUN_DIR}/modify_batchsize.py \ + python3 ${RUN_DIR}python/modify_batchsize.py \ --batch_size ${BSZ} \ --origin_model ${SIM_MODEL} \ --output_model ${FINAL_MODEL} @@ -116,7 +108,7 @@ QUANTIZED_Q_PARAMS_JSON=${CHECKPOINTS_DIR}/quant_cfg.json if [ -f $QUANTIZED_MODEL ];then echo " "Quantized Model Skip By PPQ, $QUANTIZED_MODEL has been existed else - python3 ${RUN_DIR}/quant.py \ + python3 ${RUN_DIR}python/quant.py \ --model_name ${MODEL_NAME} \ --model ${FINAL_MODEL} \ --dataset_dir ${DATASETS_DIR} \ @@ -132,7 +124,7 @@ ENGINE_FILE=${CHECKPOINTS_DIR}/${MODEL_NAME}_${PRECISION}_bs${BSZ}.engine if [ -f $ENGINE_FILE ];then echo " "Build Engine Skip, $ENGINE_FILE has been existed else - python3 ${RUN_DIR}/build_engine_by_write_qparams.py \ + python3 ${RUN_DIR}python/build_engine_by_write_qparams.py \ --onnx ${QUANTIZED_MODEL} \ --qparam_json ${QUANTIZED_Q_PARAMS_JSON} \ --engine ${ENGINE_FILE} @@ -143,7 +135,7 @@ fi let step++ echo; echo [STEP ${step}] : Inference -python3 ${RUN_DIR}/inference.py \ +python3 ${RUN_DIR}python/inference.py \ --engine_file=${ENGINE_FILE} \ --datasets_dir=${DATASETS_DIR} \ --imgsz=${IMGSIZE} \ diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_performance.sh b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_performance.sh similarity index 82% rename from models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_performance.sh rename to models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_performance.sh index 196a5090..739f62cb 100644 --- a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_performance.sh +++ b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_performance.sh @@ -44,18 +44,18 @@ do esac done -RUN_DIR=$(cd $(dirname $0); cd ../; pwd) -PROJ_DIR=$(cd $(dirname $0); cd ../../../../../../../; pwd) -DATASETS_DIR="${PROJ_DIR}/data/datasets/imagenet_val" -CHECKPOINTS_DIR="${PROJ_DIR}/data/checkpoints/mobilenetv2" +RUN_DIR=${RUN_DIR} +PROJ_DIR=${PROJ_DIR} +DATASETS_DIR=${DATASETS_DIR} +CHECKPOINTS_DIR=${CHECKPOINTS_DIR} if [ ! -d $CHECKPOINTS_DIR ]; then mkdir -p $CHECKPOINTS_DIR fi -MODEL_NAME="mobilenetv2" -ORIGINE_MODEL="${CHECKPOINTS_DIR}/raw_mobilenetv2.onnx" +MODEL_NAME="mobilenet_v2" +ORIGINE_MODEL="${CHECKPOINTS_DIR}/mobilenet_v2.onnx" echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR} echo DATASETS_DIR : ${DATASETS_DIR} @@ -69,14 +69,6 @@ step=0 # Export Onnx Model let step++ echo; -echo [STEP ${step}] : Export Onnx Model -if [ -f ${ORIGINE_MODEL} ];then - echo " "Onnx Model, ${ORIGINE_MODEL} has been existed -else - python3 ${RUN_DIR}/export_onnx.py \ - --output_model $ORIGINE_MODEL - echo " "Generate ${ORIGINE_MODEL} -fi SIM_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_sim.onnx # Simplify Model @@ -86,7 +78,7 @@ echo [STEP ${step}] : Simplify Model if [ -f ${SIM_MODEL} ];then echo " "Simplify Model, ${SIM_MODEL} has been existed else - python3 ${RUN_DIR}/simplify_model.py \ + python3 ${RUN_DIR}python/simplify_model.py \ --origin_model $ORIGINE_MODEL \ --output_model ${SIM_MODEL} echo " "Generate ${SIM_MODEL} @@ -100,7 +92,7 @@ FINAL_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_${BSZ}.onnx if [ -f $FINAL_MODEL ];then echo " "Change Batchsize Skip, $FINAL_MODEL has been existed else - python3 ${RUN_DIR}/modify_batchsize.py \ + python3 ${RUN_DIR}python/modify_batchsize.py \ --batch_size ${BSZ} \ --origin_model ${SIM_MODEL} \ --output_model ${FINAL_MODEL} @@ -116,7 +108,7 @@ QUANTIZED_Q_PARAMS_JSON=${CHECKPOINTS_DIR}/quant_cfg.json if [ -f $QUANTIZED_MODEL ];then echo " "Quantized Model Skip By PPQ, $QUANTIZED_MODEL has been existed else - python3 ${RUN_DIR}/quant.py \ + python3 ${RUN_DIR}python/quant.py \ --model_name ${MODEL_NAME} \ --model ${FINAL_MODEL} \ --dataset_dir ${DATASETS_DIR} \ @@ -132,7 +124,7 @@ ENGINE_FILE=${CHECKPOINTS_DIR}/${MODEL_NAME}_${PRECISION}_bs${BSZ}.engine if [ -f $ENGINE_FILE ];then echo " "Build Engine Skip, $ENGINE_FILE has been existed else - python3 ${RUN_DIR}/build_engine_by_write_qparams.py \ + python3 ${RUN_DIR}python/build_engine_by_write_qparams.py \ --onnx ${QUANTIZED_MODEL} \ --qparam_json ${QUANTIZED_Q_PARAMS_JSON} \ --engine ${ENGINE_FILE} @@ -143,7 +135,7 @@ fi let step++ echo; echo [STEP ${step}] : Inference -python3 ${RUN_DIR}/inference.py \ +python3 ${RUN_DIR}python/inference.py \ --engine_file=${ENGINE_FILE} \ --datasets_dir=${DATASETS_DIR} \ --imgsz=${IMGSIZE} \ diff --git a/models/cv/classification/mobilenet_v3/ixrt/README.md b/models/cv/classification/mobilenet_v3/ixrt/README.md index b1ef8f3d..1ff5e158 100644 --- a/models/cv/classification/mobilenet_v3/ixrt/README.md +++ b/models/cv/classification/mobilenet_v3/ixrt/README.md @@ -15,10 +15,7 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate +pip3 install -r requirements.txt ``` ### Download @@ -31,7 +28,7 @@ Dataset: to download the validation dat ```bash mkdir checkpoints -python3 export_onnx.py --origin_model /path/to/mobilenet_v3_small-047dcff4.pth --output_model checkpoints/mobilenetv3.onnx +python3 export_onnx.py --origin_model /path/to/mobilenet_v3_small-047dcff4.pth --output_model checkpoints/mobilenet_v3.onnx ``` ## Inference @@ -41,16 +38,16 @@ export PROJ_DIR=./ export DATASETS_DIR=/path/to/imagenet_val/ export CHECKPOINTS_DIR=./checkpoints export RUN_DIR=./ -export CONFIG_DIR=config/MOBILENETV3_CONFIG +export CONFIG_DIR=config/MOBILENET_V3_CONFIG ``` ### FP16 ```bash # Accuracy -bash scripts/infer_mobilenetv3_fp16_accuracy.sh +bash scripts/infer_mobilenet_v3_fp16_accuracy.sh # Performance -bash scripts/infer_mobilenetv3_fp16_performance.sh +bash scripts/infer_mobilenet_v3_fp16_performance.sh ``` ## Results diff --git a/models/cv/classification/mobilenet_v3/ixrt/config/MOBILENETV3_CONFIG b/models/cv/classification/mobilenet_v3/ixrt/config/MOBILENET_V3_CONFIG similarity index 97% rename from models/cv/classification/mobilenet_v3/ixrt/config/MOBILENETV3_CONFIG rename to models/cv/classification/mobilenet_v3/ixrt/config/MOBILENET_V3_CONFIG index cd971566..aef74a6c 100644 --- a/models/cv/classification/mobilenet_v3/ixrt/config/MOBILENETV3_CONFIG +++ b/models/cv/classification/mobilenet_v3/ixrt/config/MOBILENET_V3_CONFIG @@ -17,7 +17,7 @@ # ORIGINE_MODEL : 原始onnx文件名称 IMGSIZE=224 MODEL_NAME=MobileNet_v3 -ORIGINE_MODEL=mobilenetv3.onnx +ORIGINE_MODEL=mobilenet_v3.onnx # QUANT CONFIG (仅PRECISION为int8时生效) # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema] diff --git a/models/cv/classification/mobilenet_v3/ixrt/inference.py b/models/cv/classification/mobilenet_v3/ixrt/inference.py index 2c9dcb3f..50aafd4f 100644 --- a/models/cv/classification/mobilenet_v3/ixrt/inference.py +++ b/models/cv/classification/mobilenet_v3/ixrt/inference.py @@ -83,6 +83,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -104,7 +105,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/mobilenet_v3/ixrt/requirements.txt b/models/cv/classification/mobilenet_v3/ixrt/requirements.txt new file mode 100644 index 00000000..e1eda59c --- /dev/null +++ b/models/cv/classification/mobilenet_v3/ixrt/requirements.txt @@ -0,0 +1,4 @@ +tqdm +onnx +onnxsim +tabulate \ No newline at end of file diff --git a/models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenetv3_fp16_accuracy.sh b/models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenet_v3_fp16_accuracy.sh similarity index 100% rename from models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenetv3_fp16_accuracy.sh rename to models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenet_v3_fp16_accuracy.sh diff --git a/models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenetv3_fp16_performance.sh b/models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenet_v3_fp16_performance.sh similarity index 100% rename from models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenetv3_fp16_performance.sh rename to models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenet_v3_fp16_performance.sh diff --git a/models/cv/classification/res2net50/ixrt/README.md b/models/cv/classification/res2net50/ixrt/README.md index 9c381613..1ec7a251 100644 --- a/models/cv/classification/res2net50/ixrt/README.md +++ b/models/cv/classification/res2net50/ixrt/README.md @@ -15,21 +15,20 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate +pip3 install -r requirements.txt ``` ### Download +Pretrained model: + Dataset: to download the validation dataset. ### Model Conversion ```bash mkdir checkpoints -python3 export_onnx.py --output_model checkpoints/res2net50.onnx +python3 export_onnx.py --origin_model /path/to/res2net50_14w_8s-6527dddc.pth --output_model checkpoints/res2net50.onnx ``` ## Inference diff --git a/models/cv/classification/res2net50/ixrt/export_onnx.py b/models/cv/classification/res2net50/ixrt/export_onnx.py index c85685e5..ebc4a2f2 100644 --- a/models/cv/classification/res2net50/ixrt/export_onnx.py +++ b/models/cv/classification/res2net50/ixrt/export_onnx.py @@ -164,25 +164,17 @@ class Res2Net(nn.Module): return x -def res2net50_14w_8s(pretrained=False, **kwargs): - """Constructs a Res2Net-50_14w_8s model. - Args: - pretrained (bool): If True, returns a model pre-trained on ImageNet - """ - model = Res2Net(Bottle2neck, [3, 4, 6, 3], baseWidth = 14, scale = 8, **kwargs) - if pretrained: - model.load_state_dict(model_zoo.load_url(model_urls['res2net50_14w_8s'])) - return model - def parse_args(): parser = argparse.ArgumentParser() + parser.add_argument("--origin_model", type=str) parser.add_argument("--output_model", type=str) args = parser.parse_args() return args if __name__ == '__main__': args = parse_args() - model = res2net50_14w_8s(pretrained=True) + model = Res2Net(Bottle2neck, [3, 4, 6, 3], baseWidth = 14, scale = 8) + model.load_state_dict(torch.load(args.origin_model)) model.cuda() model.eval() input = torch.randn(32, 3, 224, 224, device='cuda') diff --git a/models/cv/classification/res2net50/ixrt/inference.py b/models/cv/classification/res2net50/ixrt/inference.py index 2c9dcb3f..50aafd4f 100644 --- a/models/cv/classification/res2net50/ixrt/inference.py +++ b/models/cv/classification/res2net50/ixrt/inference.py @@ -83,6 +83,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -104,7 +105,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/res2net50/ixrt/requirements.txt b/models/cv/classification/res2net50/ixrt/requirements.txt new file mode 100644 index 00000000..e1eda59c --- /dev/null +++ b/models/cv/classification/res2net50/ixrt/requirements.txt @@ -0,0 +1,4 @@ +tqdm +onnx +onnxsim +tabulate \ No newline at end of file diff --git a/models/cv/classification/resnet18/ixrt/README.md b/models/cv/classification/resnet18/ixrt/README.md index f78e7696..71857e65 100644 --- a/models/cv/classification/resnet18/ixrt/README.md +++ b/models/cv/classification/resnet18/ixrt/README.md @@ -15,21 +15,20 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate +pip3 install -r requirements.txt ``` ### Download +Pretrained model: + Dataset: to download the validation dataset. ### Model Conversion ```bash mkdir checkpoints -python3 export_onnx.py --output_model checkpoints/resnet18.onnx +python3 export_onnx.py --origin_model /path/to/resnet18-f37072fd.pth --output_model checkpoints/resnet18.onnx ``` ## Inference diff --git a/models/cv/classification/resnet18/ixrt/export_onnx.py b/models/cv/classification/resnet18/ixrt/export_onnx.py index 3f963af6..708a205a 100644 --- a/models/cv/classification/resnet18/ixrt/export_onnx.py +++ b/models/cv/classification/resnet18/ixrt/export_onnx.py @@ -18,12 +18,14 @@ import argparse def parse_args(): parser = argparse.ArgumentParser() + parser.add_argument("--origin_model", type=str) parser.add_argument("--output_model", type=str) args = parser.parse_args() return args args = parse_args() -model = models.resnet18(pretrained=True) +model = models.resnet18() +model.load_state_dict(torch.load(args.origin_model)) model.cuda() model.eval() input = torch.randn(1, 3, 224, 224, device='cuda') diff --git a/models/cv/classification/resnet18/ixrt/inference.py b/models/cv/classification/resnet18/ixrt/inference.py index 1ec56b4a..4e178df4 100644 --- a/models/cv/classification/resnet18/ixrt/inference.py +++ b/models/cv/classification/resnet18/ixrt/inference.py @@ -84,6 +84,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -105,7 +106,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/resnet18/ixrt/requirements.txt b/models/cv/classification/resnet18/ixrt/requirements.txt new file mode 100644 index 00000000..e1eda59c --- /dev/null +++ b/models/cv/classification/resnet18/ixrt/requirements.txt @@ -0,0 +1,4 @@ +tqdm +onnx +onnxsim +tabulate \ No newline at end of file diff --git a/models/cv/classification/shufflenet_v1/ixrt/README.md b/models/cv/classification/shufflenet_v1/ixrt/README.md index e29de33a..4dee5cae 100644 --- a/models/cv/classification/shufflenet_v1/ixrt/README.md +++ b/models/cv/classification/shufflenet_v1/ixrt/README.md @@ -16,17 +16,13 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install tabulate -pip3 install onnx -pip3 install onnxsim -pip3 install opencv-python==4.6.0.66 -pip3 install mmcls==0.24.0 -pip3 install mmcv==1.5.3 +pip3 install -r requirements.txt ``` ### Download +Pretrained model: + Dataset: to download the validation dataset. ### Model Conversion @@ -39,7 +35,7 @@ cd .. python3 export_onnx.py \ --config_file ./checkpoints/mmpretrain/configs/shufflenet_v1/shufflenet-v1-1x_16xb64_in1k.py \ - --checkpoint_file https://download.openmmlab.com/mmclassification/v0/shufflenet_v1/shufflenet_v1_batch1024_imagenet_20200804-5d6cec73.pth \ + --checkpoint_file ./shufflenet_v1_batch1024_imagenet_20200804-5d6cec73.pth \ --output_model ./checkpoints/shufflenet_v1.onnx ``` diff --git a/models/cv/classification/shufflenet_v1/ixrt/inference.py b/models/cv/classification/shufflenet_v1/ixrt/inference.py index 1ec56b4a..4e178df4 100644 --- a/models/cv/classification/shufflenet_v1/ixrt/inference.py +++ b/models/cv/classification/shufflenet_v1/ixrt/inference.py @@ -84,6 +84,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -105,7 +106,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/shufflenet_v1/ixrt/requirements.txt b/models/cv/classification/shufflenet_v1/ixrt/requirements.txt new file mode 100644 index 00000000..fdd84a5d --- /dev/null +++ b/models/cv/classification/shufflenet_v1/ixrt/requirements.txt @@ -0,0 +1,7 @@ +tqdm +tabulate +onnx +onnxsim +opencv-python==4.6.0.66 +mmcls==0.24.0 +mmcv==1.5.3 \ No newline at end of file diff --git a/models/cv/classification/squeezenet_1.1/ixrt/README.md b/models/cv/classification/squeezenet_v11/ixrt/README.md similarity index 87% rename from models/cv/classification/squeezenet_1.1/ixrt/README.md rename to models/cv/classification/squeezenet_v11/ixrt/README.md index 08fe037a..df5b02d4 100644 --- a/models/cv/classification/squeezenet_1.1/ixrt/README.md +++ b/models/cv/classification/squeezenet_v11/ixrt/README.md @@ -17,13 +17,7 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install tabulate -pip3 install ppq -pip3 install pycuda -pip3 install opencv-python==4.6.0.66 +pip3 install -r requirements.txt ``` ### Download @@ -36,7 +30,7 @@ Dataset: to download the validation dat ```bash mkdir checkpoints -python3 export_onnx.py --origin_model /path/to/squeezenet1_1-b8a52dc0.pth --output_model checkpoints/squeezenetv11.onnx +python3 export_onnx.py --origin_model /path/to/squeezenet1_1-b8a52dc0.pth --output_model checkpoints/squeezenet_v11.onnx ``` ## Inference diff --git a/models/cv/classification/squeezenet_1.1/ixrt/build_engine.py b/models/cv/classification/squeezenet_v11/ixrt/build_engine.py similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/build_engine.py rename to models/cv/classification/squeezenet_v11/ixrt/build_engine.py diff --git a/models/cv/classification/squeezenet_1.1/ixrt/build_i8_engine.py b/models/cv/classification/squeezenet_v11/ixrt/build_i8_engine.py similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/build_i8_engine.py rename to models/cv/classification/squeezenet_v11/ixrt/build_i8_engine.py diff --git a/models/cv/classification/squeezenet_1.1/ixrt/calibration_dataset.py b/models/cv/classification/squeezenet_v11/ixrt/calibration_dataset.py similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/calibration_dataset.py rename to models/cv/classification/squeezenet_v11/ixrt/calibration_dataset.py diff --git a/models/cv/classification/squeezenet_1.1/ixrt/common.py b/models/cv/classification/squeezenet_v11/ixrt/common.py similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/common.py rename to models/cv/classification/squeezenet_v11/ixrt/common.py diff --git a/models/cv/classification/squeezenet_1.1/ixrt/config/SQUEEZENET_V11_CONFIG b/models/cv/classification/squeezenet_v11/ixrt/config/SQUEEZENET_V11_CONFIG similarity index 95% rename from models/cv/classification/squeezenet_1.1/ixrt/config/SQUEEZENET_V11_CONFIG rename to models/cv/classification/squeezenet_v11/ixrt/config/SQUEEZENET_V11_CONFIG index efc2a087..19d35c97 100644 --- a/models/cv/classification/squeezenet_1.1/ixrt/config/SQUEEZENET_V11_CONFIG +++ b/models/cv/classification/squeezenet_v11/ixrt/config/SQUEEZENET_V11_CONFIG @@ -3,7 +3,7 @@ # ORIGINE_MODEL : 原始onnx文件名称 IMGSIZE=224 MODEL_NAME=SqueezeNet_v11 -ORIGINE_MODEL=squeezenetv11.onnx +ORIGINE_MODEL=squeezenet_v11.onnx # QUANT CONFIG (仅PRECISION为int8时生效) # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema] diff --git a/models/cv/classification/squeezenet_1.1/ixrt/export_onnx.py b/models/cv/classification/squeezenet_v11/ixrt/export_onnx.py similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/export_onnx.py rename to models/cv/classification/squeezenet_v11/ixrt/export_onnx.py diff --git a/models/cv/classification/squeezenet_1.1/ixrt/inference.py b/models/cv/classification/squeezenet_v11/ixrt/inference.py similarity index 96% rename from models/cv/classification/squeezenet_1.1/ixrt/inference.py rename to models/cv/classification/squeezenet_v11/ixrt/inference.py index 1ec56b4a..4e178df4 100644 --- a/models/cv/classification/squeezenet_1.1/ixrt/inference.py +++ b/models/cv/classification/squeezenet_v11/ixrt/inference.py @@ -84,6 +84,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -105,7 +106,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/squeezenet_1.1/ixrt/modify_batchsize.py b/models/cv/classification/squeezenet_v11/ixrt/modify_batchsize.py similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/modify_batchsize.py rename to models/cv/classification/squeezenet_v11/ixrt/modify_batchsize.py diff --git a/models/cv/classification/squeezenet_1.1/ixrt/quant.py b/models/cv/classification/squeezenet_v11/ixrt/quant.py similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/quant.py rename to models/cv/classification/squeezenet_v11/ixrt/quant.py diff --git a/models/cv/classification/squeezenet_1.1/ixrt/refine_model.py b/models/cv/classification/squeezenet_v11/ixrt/refine_model.py similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/refine_model.py rename to models/cv/classification/squeezenet_v11/ixrt/refine_model.py diff --git a/models/cv/classification/squeezenet_v11/ixrt/requirements.txt b/models/cv/classification/squeezenet_v11/ixrt/requirements.txt new file mode 100644 index 00000000..e4d443b8 --- /dev/null +++ b/models/cv/classification/squeezenet_v11/ixrt/requirements.txt @@ -0,0 +1,7 @@ +tqdm +onnx +onnxsim +tabulate +ppq +pycuda +opencv-python==4.6.0.66 \ No newline at end of file diff --git a/models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_fp16_accuracy.sh b/models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_fp16_accuracy.sh similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_fp16_accuracy.sh rename to models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_fp16_accuracy.sh diff --git a/models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_fp16_performance.sh b/models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_fp16_performance.sh similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_fp16_performance.sh rename to models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_fp16_performance.sh diff --git a/models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_int8_accuracy.sh b/models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_int8_accuracy.sh similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_int8_accuracy.sh rename to models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_int8_accuracy.sh diff --git a/models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_int8_performance.sh b/models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_int8_performance.sh similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_int8_performance.sh rename to models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_int8_performance.sh diff --git a/models/cv/classification/squeezenet_1.1/ixrt/simplify_model.py b/models/cv/classification/squeezenet_v11/ixrt/simplify_model.py similarity index 100% rename from models/cv/classification/squeezenet_1.1/ixrt/simplify_model.py rename to models/cv/classification/squeezenet_v11/ixrt/simplify_model.py diff --git a/models/cv/classification/vgg16/ixrt/README.md b/models/cv/classification/vgg16/ixrt/README.md index 370adda0..789fcc8b 100644 --- a/models/cv/classification/vgg16/ixrt/README.md +++ b/models/cv/classification/vgg16/ixrt/README.md @@ -16,20 +16,20 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-dev -pip3 install tqdm -pip3 install onnxsim -pip3 install opencv-python==4.6.0.66 +pip3 install -r requirements.txt ``` ### Download +Pretrained model: + Dataset: to download the validation dataset. ### Model Conversion ```bash mkdir checkpoints -python3 export_onnx.py --output_model checkpoints/vgg16.onnx +python3 export_onnx.py --origin_model /path/to/vgg16-397923af.pth --output_model checkpoints/vgg16.onnx ``` ## Inference diff --git a/models/cv/classification/vgg16/ixrt/export_onnx.py b/models/cv/classification/vgg16/ixrt/export_onnx.py index aa0b19ae..17d8bb55 100644 --- a/models/cv/classification/vgg16/ixrt/export_onnx.py +++ b/models/cv/classification/vgg16/ixrt/export_onnx.py @@ -18,12 +18,14 @@ import argparse def parse_args(): parser = argparse.ArgumentParser() + parser.add_argument("--origin_model", type=str) parser.add_argument("--output_model", type=str) args = parser.parse_args() return args args = parse_args() -model = models.vgg16(pretrained=True) +model = models.vgg16() +model.load_state_dict(torch.load(args.origin_model)) model.cuda() model.eval() input = torch.randn(1, 3, 224, 224, device='cuda') diff --git a/models/cv/classification/vgg16/ixrt/inference.py b/models/cv/classification/vgg16/ixrt/inference.py index 1ec56b4a..4e178df4 100644 --- a/models/cv/classification/vgg16/ixrt/inference.py +++ b/models/cv/classification/vgg16/ixrt/inference.py @@ -84,6 +84,7 @@ def main(config): total_sample = 0 acc_top1, acc_top5 = 0, 0 + start_time = time.time() with tqdm(total= len(dataloader)) as _tqdm: for idx, (batch_data, batch_label) in enumerate(dataloader): batch_data = batch_data.numpy().astype(inputs[0]["dtype"]) @@ -105,7 +106,10 @@ def main(config): _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample), acc_5='{:.4f}'.format(acc_top5/total_sample)) _tqdm.update(1) + end_time = time.time() + end2end_time = end_time - start_time + print(F"E2E time : {end2end_time:.3f} seconds") print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}") print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}") acc1 = acc_top1/total_sample diff --git a/models/cv/classification/vgg16/ixrt/requirements.txt b/models/cv/classification/vgg16/ixrt/requirements.txt new file mode 100644 index 00000000..24dc14b7 --- /dev/null +++ b/models/cv/classification/vgg16/ixrt/requirements.txt @@ -0,0 +1,3 @@ +tqdm +onnxsim +opencv-python==4.6.0.66 \ No newline at end of file diff --git a/models/cv/detection/yolov8/igie/README.md b/models/cv/detection/yolov8/igie/README.md index ce5ce80d..cb2a3594 100644 --- a/models/cv/detection/yolov8/igie/README.md +++ b/models/cv/detection/yolov8/igie/README.md @@ -18,7 +18,7 @@ apt install -y libgl1-mesa-dev pip3 install tqdm pip3 install onnx pip3 install pycocotools -pip3 install ultralytics +pip3 install ultralytics==8.2.51 ``` ### Download diff --git a/models/cv/detection/yolov8/ixrt/README.md b/models/cv/detection/yolov8/ixrt/README.md index 96d637e0..6ed7ea53 100644 --- a/models/cv/detection/yolov8/ixrt/README.md +++ b/models/cv/detection/yolov8/ixrt/README.md @@ -15,12 +15,7 @@ yum install -y mesa-libGL ## Ubuntu apt install -y libgl1-mesa-glx -pip3 install tqdm -pip3 install onnx -pip3 install onnxsim -pip3 install pycocotools -pip3 install ultralytics -pip3 install cuda-python +pip3 install -r requirements.txt ``` ### Download @@ -29,39 +24,40 @@ Pretrained model: to download the validation dataset. -```bash -# get yolov8n.pt -wget https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt -# set coco path -mkdir -p data/ -ln -s /Path/to/coco/ data/coco -``` - ### Model Conversion ```bash -python3 export.py --weight yolov8n.pt --batch 32 -onnxsim yolov8n.onnx ./data/yolov8n.onnx +mkdir -p checkpoints/ +mv yolov8n.pt yolov8.pt +python3 export.py --weight yolov8.pt --batch 32 +onnxsim yolov8.onnx ./checkpoints/yolov8.onnx ``` ## Inference +```bash +export PROJ_DIR=./ +export DATASETS_DIR=/path/to/coco/ +export CHECKPOINTS_DIR=./checkpoints +export RUN_DIR=./ +``` + ### FP16 ```bash # Accuracy -bash scripts/infer_yolov8n_fp16_accuracy.sh +bash scripts/infer_yolov8_fp16_accuracy.sh # Performance -bash scripts/infer_yolov8n_fp16_performance.sh +bash scripts/infer_yolov8_fp16_performance.sh ``` ### INT8 ```bash # Accuracy -bash scripts/infer_yolov8n_int8_accuracy.sh +bash scripts/infer_yolov8_int8_accuracy.sh # Performance -bash scripts/infer_yolov8n_int8_performance.sh +bash scripts/infer_yolov8_int8_performance.sh ``` ## Results diff --git a/models/cv/detection/yolov8/ixrt/requirements.txt b/models/cv/detection/yolov8/ixrt/requirements.txt new file mode 100644 index 00000000..cc201ca4 --- /dev/null +++ b/models/cv/detection/yolov8/ixrt/requirements.txt @@ -0,0 +1,6 @@ +tqdm +onnx +onnxsim +pycocotools +ultralytics==8.2.51 +cuda-python \ No newline at end of file diff --git a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_accuracy.sh b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_accuracy.sh similarity index 88% rename from models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_accuracy.sh rename to models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_accuracy.sh index 44e75376..65434fec 100644 --- a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_accuracy.sh +++ b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_accuracy.sh @@ -22,27 +22,27 @@ check_status() fi } -PROJ_DIR=$(cd $(dirname $0);cd ../; pwd) -DATASETS_DIR="${PROJ_DIR}/data/coco" +PROJ_DIR=${PROJ_DIR} +DATASETS_DIR=${DATASETS_DIR} COCO_GT=${DATASETS_DIR}/annotations/instances_val2017.json EVAL_DIR=${DATASETS_DIR}/images/val2017 -CHECKPOINTS_DIR="${PROJ_DIR}/data" -RUN_DIR="${PROJ_DIR}" +CHECKPOINTS_DIR=${CHECKPOINTS_DIR} +RUN_DIR=${PROJ_DIR} ORIGINE_MODEL=${CHECKPOINTS_DIR} echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR} echo DATASETS_DIR : ${DATASETS_DIR} echo RUN_DIR : ${RUN_DIR} echo ====================== Model Info ====================== -echo Model Name : yolov8n +echo Model Name : yolov8 echo Onnx Path : ${ORIGINE_MODEL} BATCH_SIZE=32 -CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8n.onnx +CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8.onnx # Build Engine echo Build Engine -ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8n_fp16.engine +ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8_fp16.engine if [ -f $ENGINE_FILE ];then echo " "Build Engine Skip, $ENGINE_FILE has been existed else diff --git a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_performance.sh b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_performance.sh similarity index 88% rename from models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_performance.sh rename to models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_performance.sh index 1ab3808f..355b27bc 100644 --- a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_performance.sh +++ b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_performance.sh @@ -22,27 +22,27 @@ check_status() fi } -PROJ_DIR=$(cd $(dirname $0);cd ../; pwd) -DATASETS_DIR="${PROJ_DIR}/data/coco" +PROJ_DIR=${PROJ_DIR} +DATASETS_DIR=${DATASETS_DIR} COCO_GT=${DATASETS_DIR}/annotations/instances_val2017.json EVAL_DIR=${DATASETS_DIR}/images/val2017 -CHECKPOINTS_DIR="${PROJ_DIR}/data" -RUN_DIR="${PROJ_DIR}" +CHECKPOINTS_DIR=${CHECKPOINTS_DIR} +RUN_DIR=${PROJ_DIR} ORIGINE_MODEL=${CHECKPOINTS_DIR} echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR} echo DATASETS_DIR : ${DATASETS_DIR} echo RUN_DIR : ${RUN_DIR} echo ====================== Model Info ====================== -echo Model Name : yolov8n +echo Model Name : yolov8 echo Onnx Path : ${ORIGINE_MODEL} BATCH_SIZE=32 -CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8n.onnx +CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8.onnx # Build Engine echo Build Engine -ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8n_fp16.engine +ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8_fp16.engine if [ -f $ENGINE_FILE ];then echo " "Build Engine Skip, $ENGINE_FILE has been existed else diff --git a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_accuracy.sh b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_accuracy.sh similarity index 90% rename from models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_accuracy.sh rename to models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_accuracy.sh index a2257463..bf1ecf25 100644 --- a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_accuracy.sh +++ b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_accuracy.sh @@ -22,12 +22,12 @@ check_status() fi } -PROJ_DIR=$(cd $(dirname $0);cd ../; pwd) -DATASETS_DIR="${PROJ_DIR}/data/coco" +PROJ_DIR=${PROJ_DIR} +DATASETS_DIR=${DATASETS_DIR} COCO_GT=${DATASETS_DIR}/annotations/instances_val2017.json EVAL_DIR=${DATASETS_DIR}/images/val2017 -CHECKPOINTS_DIR="${PROJ_DIR}/data" -RUN_DIR="${PROJ_DIR}" +CHECKPOINTS_DIR=${CHECKPOINTS_DIR} +RUN_DIR=${PROJ_DIR} ORIGINE_MODEL=${CHECKPOINTS_DIR} DISABLE_NAMES=('/model.22/Concat' '/model.22/Concat_1' '/model.22/Concat_2' '/model.22/Reshape' '/model.22/Reshape_1' '/model.22/Reshape_2' '/model.22/Concat_3' '/model.22/Split' '/model.22/dfl/Reshape' '/model.22/dfl/Transpose' '/model.22/dfl/Softmax' '/model.22/dfl/Transpose_1' '/model.22/dfl/conv/Conv' '/model.22/dfl/Reshape_1' '/model.22/Slice' '/model.22/Slice_1' '/model.22/Sub' '/model.22/Add_1' '/model.22/Add_2' '/model.22/Div_1' '/model.22/Sub_1' '/model.22/Concat_4' '/model.22/Mul_2' '/model.22/Sigmoid' '/model.22/Concat_5') @@ -35,19 +35,19 @@ echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR} echo DATASETS_DIR : ${DATASETS_DIR} echo RUN_DIR : ${RUN_DIR} echo ====================== Model Info ====================== -echo Model Name : yolov8n +echo Model Name : yolov8 echo Onnx Path : ${ORIGINE_MODEL} BATCH_SIZE=32 -CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8n.onnx +CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8.onnx # quant -FINAL_MODEL=${CHECKPOINTS_DIR}/quantized_yolov8n_bs${BATCH_SIZE}.onnx +FINAL_MODEL=${CHECKPOINTS_DIR}/quantized_yolov8_bs${BATCH_SIZE}.onnx if [ -f $FINAL_MODEL ];then echo " "Quantize Skip, $FINAL_MODEL has been existed else python3 ${RUN_DIR}/quant.py \ - --model_name "YOLOV8N" \ + --model_name "YOLOV8" \ --model ${CURRENT_MODEL} \ --bsz ${BATCH_SIZE} \ --dataset_dir ${EVAL_DIR} \ @@ -62,7 +62,7 @@ CURRENT_MODEL=${FINAL_MODEL} # Build Engine echo Build Engine -ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8n_int8.engine +ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8_int8.engine if [ -f $ENGINE_FILE ];then echo " "Build Engine Skip, $ENGINE_FILE has been existed else diff --git a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_performance.sh b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_performance.sh similarity index 89% rename from models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_performance.sh rename to models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_performance.sh index f1774d5b..f4c31b68 100644 --- a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_performance.sh +++ b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_performance.sh @@ -22,31 +22,31 @@ check_status() fi } -PROJ_DIR=$(cd $(dirname $0);cd ../; pwd) -DATASETS_DIR="${PROJ_DIR}/data/coco" +PROJ_DIR=${PROJ_DIR} +DATASETS_DIR=${DATASETS_DIR} COCO_GT=${DATASETS_DIR}/annotations/instances_val2017.json EVAL_DIR=${DATASETS_DIR}/images/val2017 -CHECKPOINTS_DIR="${PROJ_DIR}/data" -RUN_DIR="${PROJ_DIR}" +CHECKPOINTS_DIR=${CHECKPOINTS_DIR} +RUN_DIR=${PROJ_DIR} ORIGINE_MODEL=${CHECKPOINTS_DIR} echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR} echo DATASETS_DIR : ${DATASETS_DIR} echo RUN_DIR : ${RUN_DIR} echo ====================== Model Info ====================== -echo Model Name : yolov8n +echo Model Name : yolov8 echo Onnx Path : ${ORIGINE_MODEL} BATCH_SIZE=32 -CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8n.onnx +CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8.onnx # quant -FINAL_MODEL=${CHECKPOINTS_DIR}/quantized_yolov8n_bs${BATCH_SIZE}.onnx +FINAL_MODEL=${CHECKPOINTS_DIR}/quantized_yolov8_bs${BATCH_SIZE}.onnx if [ -f $FINAL_MODEL ];then echo " "Quantize Skip, $FINAL_MODEL has been existed else python3 ${RUN_DIR}/quant.py \ - --model_name "YOLOV8N" \ + --model_name "YOLOV8" \ --model ${CURRENT_MODEL} \ --bsz ${BATCH_SIZE} \ --dataset_dir ${EVAL_DIR} \ @@ -61,7 +61,7 @@ CURRENT_MODEL=${FINAL_MODEL} # Build Engine echo Build Engine -ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8n_int8.engine +ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8_int8.engine if [ -f $ENGINE_FILE ];then echo " "Build Engine Skip, $ENGINE_FILE has been existed else -- Gitee