Fixes for intel mlperf inference retinanet

anandhu-eng · Jun 29, 2024 · 47ed8c5 · 47ed8c5
1 parent af02a2c
commit 47ed8c5
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Showing 6 changed files with 8 additions and 43 deletions.
diff --git a/script/app-mlperf-inference-intel/_cm.yaml b/script/app-mlperf-inference-intel/_cm.yaml
@@ -410,7 +410,7 @@ variations:
         tags: _name.retinanet-pt
     deps:
       - tags: get,conda,_name.retinanet-pt
-      - tags: get,python,_conda.resnet50-pt
+      - tags: get,python,_conda.retinanet-pt
         adr:
           conda-python:
             version: "3.9"

diff --git a/script/app-mlperf-inference-intel/customize.py b/script/app-mlperf-inference-intel/customize.py
@@ -76,6 +76,8 @@ def preprocess(i):
     elif env['CM_LOCAL_MLPERF_INFERENCE_INTEL_RUN_MODE'] == "compilation":
         if master_model == "resnet50":
             i['run_script_input']['script_name'] = "compile_resnet50"
+        elif master_model == "retinanet":
+            i['run_script_input']['script_name'] = "compile_retinanet"
 
     elif env['CM_LOCAL_MLPERF_INFERENCE_INTEL_RUN_MODE'] == "build_harness":
         print(f"Harness Root: {harness_root}")

diff --git a/script/get-preprocessed-dataset-generic/src/preprocess_object_detection_dataset.py b/script/get-preprocessed-dataset-generic/src/preprocess_object_detection_dataset.py
@@ -38,7 +38,7 @@ def load_image(image_path, target_size, data_type='uint8', convert_to_bgr=False,
 
 def quantize_to_uint8(image, scale, offset):
     quantized_image = (image.astype(np.float64) / scale + offset).astype(np.float64)
-    output = np.round_(quantized_image)
+    output = np.round(quantized_image)
     output = np.clip(output, 0, 255)
     return output.astype(np.uint8)
 

diff --git a/script/install-pytorch-from-src/_cm.json b/script/install-pytorch-from-src/_cm.json
@@ -129,7 +129,7 @@
       "env": {
         "CM_CONDA_ENV": "yes",
         "CM_MLPERF_INFERENCE_INTEL": "yes",
-        "CM_MLPERF_INFERENCE_INTEL_RESNET50_MODEL": "yes",
+        "CM_MLPERF_INFERENCE_INTEL_MODEL": "resnet50",
         "USE_CUDA": "0"
       },
       "deps": [
@@ -196,7 +196,7 @@
       "env": {
         "CM_CONDA_ENV": "yes",
         "CM_MLPERF_INFERENCE_INTEL": "yes",
-        "CM_MLPERF_INFERENCE_INTEL_RETINANET_MODEL": "yes",
+        "CM_MLPERF_INFERENCE_INTEL_MODEL": "retinanet",
         "USE_CUDA": "0"
       },
       "deps": [

diff --git a/script/install-pytorch-from-src/customize.py b/script/install-pytorch-from-src/customize.py
@@ -15,8 +15,8 @@ def preprocess(i):
         run_cmd="CC=clang CXX=clang++ USE_CUDA=OFF python -m pip install -e . "
 
         env['CM_RUN_CMD'] = run_cmd
-    elif env.get('CM_MLPERF_INFERENCE_INTEL_RESNET50_MODEL', '') == "yes":
-        i['run_script_input']['script_name'] = "run-intel-mlperf-inference-resnet50"
+    elif env.get('CM_MLPERF_INFERENCE_INTEL_MODEL', '') in [ "resnet50", "retinanet" ]:
+        i['run_script_input']['script_name'] = "run-intel-mlperf-inference-vision"
         run_cmd="CC=clang CXX=clang++ USE_CUDA=OFF python -m pip install -e . "
         run_cmd=f"CC={env['CM_C_COMPILER_WITH_PATH']} CXX={env['CM_CXX_COMPILER_WITH_PATH']} USE_CUDA=OFF python -m pip install -e . "
 

diff --git a/script/install-pytorch-from-src/run-intel-mlperf-inference-resnet50.sh b/script/install-pytorch-from-src/run-intel-mlperf-inference-resnet50.sh