Enable conv nchw-to-nhwc flag by default for most models + minor fixes (#584)

shark/iree_utils/compile_utils.py

@@ -15,6 +15,7 @@ import iree.runtime as ireert
 import iree.compiler as ireec
 from shark.iree_utils._common import iree_device_map, iree_target_map
 from shark.iree_utils.benchmark_utils import *
+from shark.parser import shark_args
 import numpy as np
 import os
 import re
@@ -66,6 +67,16 @@ def get_iree_common_args():
     ]
 
 
+# Args that are suitable only for certain models or groups of models.
+# shark_args are passed down from pytests to control which models compile with these flags,
+# but they can also be set in shark/parser.py
+def get_model_specific_args():
+    ms_args = []
+    if shark_args.enable_conv_transform == True:
+        ms_args += ["--iree-flow-enable-conv-nchw-to-nhwc-transform"]
+    return ms_args
+
+
 def create_dispatch_dirs(bench_dir, device):
     protected_files = ["ordered-dispatches.txt"]
     bench_dir_path = bench_dir.split("/")
@@ -213,14 +224,22 @@ def compile_benchmark_dirs(bench_dir, device, dispatch_benchmarks):
 
 
 def compile_module_to_flatbuffer(
-    module, device, frontend, func_name, model_config_path, extra_args
+    module,
+    device,
+    frontend,
+    func_name,
+    model_config_path,
+    extra_args,
+    model_name="None",
 ):
     # Setup Compile arguments wrt to frontends.
     input_type = ""
     args = get_iree_frontend_args(frontend)
     args += get_iree_device_args(device, extra_args)
     args += get_iree_common_args()
+    args += get_model_specific_args()
     args += extra_args
+    print(args)
 
     if frontend in ["tensorflow", "tf"]:
         input_type = "mhlo"

shark/parser.py

@@ -105,4 +105,11 @@ parser.add_argument(
     help='directory where you want to store dispatch data generated with "--dispatch_benchmarks"',
 )
 
+parser.add_argument(
+    "--enable_conv_transform",
+    default=True,
+    action="store",
+    help="Enables the --iree-flow-enable-conv-nchw-to-nhwc-transform flag.",
+)
+
 shark_args, unknown = parser.parse_known_args()

tank/model_utils.py

@@ -143,14 +143,14 @@ def get_vision_model(torch_model):
     import torchvision.models as models
 
     vision_models_dict = {
-        "alexnet": models.alexnet(pretrained=True),
-        "resnet18": models.resnet18(pretrained=True),
-        "resnet50": models.resnet50(pretrained=True),
-        "resnet101": models.resnet101(pretrained=True),
-        "squeezenet1_0": models.squeezenet1_0(pretrained=True),
-        "wide_resnet50_2": models.wide_resnet50_2(pretrained=True),
-        "mobilenet_v3_small": models.mobilenet_v3_small(pretrained=True),
-        "mnasnet1_0": models.mnasnet1_0(pretrained=True),
+        "alexnet": models.alexnet(weights="DEFAULT"),
+        "resnet18": models.resnet18(weights="DEFAULT"),
+        "resnet50": models.resnet50(weights="DEFAULT"),
+        "resnet101": models.resnet101(weights="DEFAULT"),
+        "squeezenet1_0": models.squeezenet1_0(weights="DEFAULT"),
+        "wide_resnet50_2": models.wide_resnet50_2(weights="DEFAULT"),
+        "mobilenet_v3_small": models.mobilenet_v3_small(weights="DEFAULT"),
+        "mnasnet1_0": models.mnasnet1_0(weights="DEFAULT"),
     }
     if isinstance(torch_model, str):
         torch_model = vision_models_dict[torch_model]

tank/test_models.py

@@ -127,8 +127,11 @@ class SharkModuleTester:
         self.config = config
 
     def create_and_check_module(self, dynamic, device):
+
         shark_args.local_tank_cache = self.local_tank_cache
         shark_args.update_tank = self.update_tank
+        if self.config["model_name"] in ["alexnet", "resnet18"]:
+            shark_args.enable_conv_transform = False
         model, func_name, inputs, golden_out = download_model(
             self.config["model_name"],
             tank_url=self.tank_url,
@@ -347,7 +350,16 @@ class SharkModuleTest(unittest.TestCase):
             pytest.xfail(
                 reason="Numerics Issues: https://github.com/nod-ai/SHARK/issues/388"
             )
-        if config["model_name"] == "mobilenet_v3_small":
+        if config["model_name"] == "mobilenet_v3_small" and device not in [
+            "cpu"
+        ]:
+            pytest.xfail(
+                reason="Numerics Issues: https://github.com/nod-ai/SHARK/issues/388"
+            )
+        if config["model_name"] == "mnasnet1_0" and device not in [
+            "cpu",
+            "cuda",
+        ]:
             pytest.xfail(
                 reason="Numerics Issues: https://github.com/nod-ai/SHARK/issues/388"
             )