update model's compile depth (#676)

tenstorrent · Nov 13, 2024 · 33d674b · 33d674b
1 parent bb22c1b
commit 33d674b
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Showing 5 changed files with 12 additions and 12 deletions.
diff --git a/forge/test/model_demos/high_prio/cnn/pytorch/test_blazepose.py b/forge/test/model_demos/high_prio/cnn/pytorch/test_blazepose.py
@@ -24,7 +24,7 @@
 def test_blazepose_detector_pytorch(test_device):
     # Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     # Load BlazePose Detector
     pose_detector = BlazePose()
@@ -46,7 +46,7 @@ def test_blazepose_detector_pytorch(test_device):
 def test_blazepose_regressor_pytorch(test_device):
     # Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     # Load BlazePose Landmark Regressor
     pose_regressor = BlazePoseLandmark()
@@ -61,7 +61,7 @@ def test_blaze_palm_pytorch(test_device):
 
     # Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     # Load BlazePalm Detector
     palm_detector = BlazePalm()
@@ -85,7 +85,7 @@ def test_blaze_hand_pytorch(test_device):
 
     # Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     # Load BlazePalm Detector
     hand_regressor = BlazeHandLandmark()

diff --git a/forge/test/model_demos/high_prio/cnn/pytorch/test_mobilenet_v1.py b/forge/test/model_demos/high_prio/cnn/pytorch/test_mobilenet_v1.py
@@ -167,7 +167,7 @@ def test_mobilenetv1_basic(test_device):
 def generate_model_mobilenetv1_imgcls_hf_pytorch(test_device, variant):
     # Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()  # load global compiler config object
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     # Create Forge module from PyTorch model
     preprocessor = download_model(AutoImageProcessor.from_pretrained, variant)
@@ -196,7 +196,7 @@ def test_mobilenetv1_192(test_device):
 def generate_model_mobilenetV1I224_imgcls_hf_pytorch(test_device, variant):
     # Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     # Create Forge module from PyTorch model
     preprocessor = download_model(AutoImageProcessor.from_pretrained, variant)

diff --git a/forge/test/model_demos/high_prio/cnn/pytorch/test_mobilenet_v2.py b/forge/test/model_demos/high_prio/cnn/pytorch/test_mobilenet_v2.py
@@ -47,7 +47,7 @@ def test_mobilenetv2_basic(test_device):
 def generate_model_mobilenetV2I96_imgcls_hf_pytorch(test_device, variant):
     # Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     preprocessor = download_model(AutoImageProcessor.from_pretrained, variant)
     model = download_model(AutoModelForImageClassification.from_pretrained, variant)
@@ -73,7 +73,7 @@ def test_mobilenetv2_96(test_device):
 def generate_model_mobilenetV2I160_imgcls_hf_pytorch(test_device, variant):
     # Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     preprocessor = download_model(AutoImageProcessor.from_pretrained, variant)
     model = download_model(AutoModelForImageClassification.from_pretrained, variant)
@@ -99,7 +99,7 @@ def test_mobilenetv2_160(test_device):
 def generate_model_mobilenetV2I244_imgcls_hf_pytorch(test_device, variant):
     # Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     # Create Forge module from PyTorch model
     preprocessor = download_model(AutoImageProcessor.from_pretrained, variant)
@@ -169,7 +169,7 @@ def generate_model_mobilenetV2_semseg_hf_pytorch(test_device, variant):
 
     # Configurations
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     # Load model
     framework_model = download_model(MobileNetV2ForSemanticSegmentation.from_pretrained, variant)

diff --git a/forge/test/model_demos/high_prio/cnn/pytorch/test_tri_basic_2.py b/forge/test/model_demos/high_prio/cnn/pytorch/test_tri_basic_2.py
@@ -20,7 +20,7 @@ def test_tri_basic_2_sematic_segmentation_pytorch(test_device):
 
     # Set PyBuda configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()
-    compiler_cfg.compile_depth = forge.CompileDepth.GENERATE_INITIAL_GRAPH
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     # Sample Input
     image_w = 800

diff --git a/forge/test/model_demos/high_prio/cnn/pytorch/test_yolo_v3.py b/forge/test/model_demos/high_prio/cnn/pytorch/test_yolo_v3.py
@@ -20,7 +20,7 @@
 def generate_model_yolotinyV3_imgcls_holli_pytorch(test_device, variant):
     # STEP 1: Set Forge configuration parameters
     compiler_cfg = forge.config._get_global_compiler_config()  # load global compiler config object
-    compiler_cfg.compile_depth = forge.CompileDepth.INIT_COMPILE
+    compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
 
     model = Yolov3Tiny(num_classes=80, use_wrong_previous_anchors=True)
     model.load_state_dict(torch.load("weights/yolov3_tiny_coco_01.h5"))