use unique path for test

python/tvm/contrib/msc/core/utils/file.py

@@ -61,7 +61,7 @@ class MSCDirectory(object):
 
     def __init__(self, path: str = None, keep_history: bool = True, cleanup: bool = False):
         if not path:
-            path = "msc_" + str(datetime.datetime.now().strftime("%Y%m%d_%H-%M-%S"))
+            path = "msc_" + str(datetime.datetime.now().strftime("%Y%m%d_%H%M%S"))
         self._path = os.path.abspath(path)
         self._cleanup = cleanup
         self._cwd = os.getcwd()

tests/python/contrib/test_msc/test_manager.py

@@ -18,6 +18,7 @@
 """ Test Managers in MSC. """
 
 import json
+import datetime
 import pytest
 import torch
 
@@ -34,8 +35,12 @@
 
 def _get_config(model_type, compile_type, inputs, outputs, atol=1e-1, rtol=1e-1):
     """Get msc config"""
+
+    path = "test_manager_{}_{}_{}".format(
+        model_type, compile_type, datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+    )
     return {
-        "workspace": msc_utils.msc_dir(),
+        "workspace": msc_utils.msc_dir(path),
         "verbose": "critical",
         "model_type": model_type,
         "inputs": inputs,
@@ -55,6 +60,7 @@ def _get_config(model_type, compile_type, inputs, outputs, atol=1e-1, rtol=1e-1)
 
 def _get_torch_model(name, is_training=False):
     """Get model from torch vision"""
+
     # pylint: disable=import-outside-toplevel
     try:
         import torchvision
@@ -72,6 +78,7 @@ def _get_torch_model(name, is_training=False):
 
 def _get_tf_graph():
     """Get graph from tensorflow"""
+
     # pylint: disable=import-outside-toplevel
     try:
         from tvm.contrib.msc.framework.tensorflow import tf_v1

tests/python/contrib/test_msc/test_runner.py

@@ -17,6 +17,7 @@
 
 """ Test Runners in MSC. """
 
+import datetime
 import pytest
 import numpy as np
 
@@ -41,6 +42,7 @@
 
 def _get_torch_model(name, is_training=False):
     """Get model from torch vision"""
+
     # pylint: disable=import-outside-toplevel
     try:
         import torchvision
@@ -82,7 +84,10 @@ def _test_from_torch(runner_cls, device, is_training=False, atol=1e-1, rtol=1e-1
 
     torch_model = _get_torch_model("resnet50", is_training)
     if torch_model:
-        workspace = msc_utils.set_workspace(msc_utils.msc_dir())
+        path = "test_runner_torch_{}_{}_{}".format(
+            runner_cls.__name__, device, datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+        )
+        workspace = msc_utils.set_workspace(msc_utils.msc_dir(path))
         log_path = workspace.relpath("MSC_LOG", keep_history=False)
         msc_utils.set_global_logger("info", log_path)
         input_info = [([1, 3, 224, 224], "float32")]
@@ -139,7 +144,8 @@ def test_tensorflow_runner():
 
     tf_graph, graph_def = _get_tf_graph()
     if tf_graph and graph_def:
-        workspace = msc_utils.set_workspace(msc_utils.msc_dir())
+        path = "test_runner_tf_" + str(datetime.datetime.now().strftime("%Y%m%d_%H%M%S"))
+        workspace = msc_utils.set_workspace(msc_utils.msc_dir(path))
         log_path = workspace.relpath("MSC_LOG", keep_history=False)
         msc_utils.set_global_logger("info", log_path)
         data = np.random.uniform(size=(1, 224, 224, 3)).astype("float32")

tests/python/contrib/test_msc/test_tools.py

@@ -18,6 +18,7 @@
 """ Test Tools in MSC. """
 
 import json
+import datetime
 import pytest
 import torch
 
@@ -44,8 +45,15 @@ def _get_config(
     optimize_type=None,
 ):
     """Get msc config"""
+
+    path = "test_tool_{}_{}".format(model_type, compile_type)
+    for t_type, config in tools_config.items():
+        path = path + "_" + str(t_type)
+        if "gym_configs" in config:
+            path = path + "_gym"
+    path = path + "_" + str(datetime.datetime.now().strftime("%Y%m%d_%H%M%S"))
     return {
-        "workspace": msc_utils.msc_dir(),
+        "workspace": msc_utils.msc_dir(path),
         "verbose": "critical",
         "model_type": model_type,
         "inputs": inputs,
@@ -70,6 +78,7 @@ def _get_config(
 
 def get_tool_config(tool_type, use_distill=False, use_gym=False):
     """Get config for the tool"""
+
     config = {}
     if tool_type == ToolType.PRUNER:
         config = {
@@ -178,6 +187,7 @@ def get_tool_config(tool_type, use_distill=False, use_gym=False):
 
 def _get_torch_model(name, is_training=False):
     """Get model from torch vision"""
+
     # pylint: disable=import-outside-toplevel
     try:
         import torchvision
@@ -239,6 +249,7 @@ def _test_from_torch(
 
 def get_model_info(compile_type):
     """Get the model info"""
+
     if compile_type == MSCFramework.TVM:
         return {
             "inputs": [