removed deprecated latency observer

.flake8

@@ -0,0 +1,5 @@
+[flake8]
+ignore = E203, E266, E501, W503
+max-line-length = 80
+max-complexity = 18
+select = B,C,E,F,W,T4,B9

.gitignore

@@ -121,7 +121,8 @@ dmypy.json
 .LSOverride
 
 # Icon must end with two \r
-Icon
+Icon
+
 
 # Thumbnails
 ._*
@@ -182,3 +183,4 @@ $RECYCLE.BIN/
 # .nfs files are created when an open file is removed but is still being accessed
 .nfs*
 
+.vscode

requirements.txt

@@ -1,19 +1,2 @@
-appdirs==1.4.3
-astroid==2.2.5
-attrs==19.1.0
-black==19.3b0
-Click==7.0
-isort==4.3.21
-lazy-object-proxy==1.4.1
-mccabe==0.6.1
-mypy==0.711
-mypy-extensions==0.4.1
-numpy==1.16.4
-Pillow==6.1.0
-pkg-resources==0.0.0
-six==1.12.0
-toml==0.10.0
-torch==1.1.0
-torchvision==0.3.0
-typed-ast==1.4.0
-wrapt==1.11.2
+torch>=1.1.0
+torchvision>=0.3.0

setup.py

@@ -1,11 +1,31 @@
+import codecs
+import os
+import re
 import setuptools
 
-with open("README.md", "r") as fh:
-    long_description = fh.read()
+here = os.path.abspath(os.path.dirname(__file__))
+
+
+def read(*parts):
+    with codecs.open(os.path.join(here, *parts), "r") as fp:
+        return fp.read()
+
+
+def find_version(*file_paths):
+    version_file = read(*file_paths)
+    version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", version_file, re.M)
+    if version_match:
+        return version_match.group(1)
+
+    raise RuntimeError("Unable to find version string.")
+
+
+long_description = read("README.md")
+version = find_version("torchprof", "__init__.py")
 
 setuptools.setup(
     name="torchprof",
-    version="0.3.1",
+    version=version,
     author="Alexander Wong",
     author_email="alex@udia.ca",
     description="Measure neural network device specific metrics (latency, flops, etc.)",
@@ -14,12 +34,14 @@
     url="https://github.com/awwong1/torchprof",
     packages=setuptools.find_packages(),
     license="MIT",
-    install_requires=[
-        "torch>=1.1.0,<2"
-    ],
+    install_requires=["torch>=1.1.0,<2"],
     classifiers=[
-        "Programming Language :: Python :: 3",
         "License :: OSI Approved :: MIT License",
-        "Operating System :: OS Independent"
+        "Operating System :: OS Independent",
+        "Programming Language :: Python :: 3",
+        "Programming Language :: Python :: 3.5",
+        "Programming Language :: Python :: 3.6",
+        "Programming Language :: Python :: 3.7",
+        "Programming Language :: Python :: 3.8",
     ],
-)
+)

tests/test_profile.py

@@ -2,7 +2,6 @@
 import torch
 import torchprof
 import torchvision
-import pprint
 
 
 class TestProfile(unittest.TestCase):
@@ -137,7 +136,9 @@ def test_cpu_profile_structure(self):
     def test_cuda_profile_structure(self):
         model = torchvision.models.alexnet(pretrained=False).cuda()
         x = torch.rand([1, 3, 224, 224]).cuda()
-        self._profile_structure(model, x, use_cuda=True, alexnet_ops=self.alexnet_gpu_ops)
+        self._profile_structure(
+            model, x, use_cuda=True, alexnet_ops=self.alexnet_gpu_ops
+        )
 
     def _profile_structure(self, model, x, use_cuda=False, alexnet_ops=[]):
         with torchprof.Profile(model, use_cuda=use_cuda) as prof:
@@ -164,4 +165,4 @@ def _profile_structure(self, model, x, use_cuda=False, alexnet_ops=[]):
         self.assertIsInstance(pretty, str)
         self.assertIsInstance(pretty_full, str)
 
-        # pprint.pprint(pretty)
+        # pprint.pprint(pretty)

tests/test_set_paths.py

@@ -3,6 +3,7 @@
 import torchprof
 import torchvision
 
+
 class TestSetPaths(unittest.TestCase):
     def test_cpu_profile_structure(self):
         model = torchvision.models.alexnet(pretrained=False)

torchprof/__init__.py

@@ -1,7 +1,6 @@
-name = "torchprof"
-
-from torchprof.latency_observer import LatencyObserver
 from torchprof.profile import Profile
 
-__all__ = ["LatencyObserver", "Profile"]
-__version__ = "0.3.1"
+name = "torchprof"
+
+__all__ = ["Profile"]
+__version__ = "0.3.1"

torchprof/profile.py

@@ -52,15 +52,19 @@ def __exit__(self, exc_type, exc_val, exc_tb):
 
     def __str__(self):
         if self.exited:
-            return traces_to_display(self.traces, self.trace_profile_events, paths=self.paths)
+            return traces_to_display(
+                self.traces, self.trace_profile_events, paths=self.paths
+            )
         return "<unfinished torchprof.profile>"
 
     def __call__(self, *args, **kwargs):
         return self._model(*args, **kwargs)
 
     def _hook_trace(self, trace):
         [path, leaf, module] = trace
-        if (self.paths is not None and path in self.paths) or (self.paths is None and leaf):
+        if (self.paths is not None and path in self.paths) or (
+            self.paths is None and leaf
+        ):
             _forward = module.forward
             self._forwards[path] = _forward
 
@@ -79,7 +83,9 @@ def wrap_forward(*args, **kwargs):
 
     def _remove_hook_trace(self, trace):
         [path, leaf, module] = trace
-        if (self.paths is not None and path in self.paths) or (self.paths is None and leaf):
+        if (self.paths is not None and path in self.paths) or (
+            self.paths is None and leaf
+        ):
             module.forward = self._forwards[path]
 
     def raw(self):
@@ -89,18 +95,21 @@ def raw(self):
     def display(self, show_events=False):
         if self.exited:
             return traces_to_display(
-                self.traces, self.trace_profile_events, show_events=show_events, paths=self.paths
+                self.traces,
+                self.trace_profile_events,
+                show_events=show_events,
+                paths=self.paths,
             )
         return "<unfinished torchprof.profile>"
 
 
 def flatten_tree(t, depth=0):
-    l = []
+    flat = []
     for name, st in t.items():
         measures = st.pop(None, None)
-        l.append([depth, name, measures])
-        l.extend(flatten_tree(st, depth=depth + 1))
-    return l
+        flat.append([depth, name, measures])
+        flat.extend(flatten_tree(st, depth=depth + 1))
+    return flat
 
 
 def traces_to_display(traces, trace_events, show_events=False, paths=None):
@@ -116,7 +125,9 @@ def traces_to_display(traces, trace_events, show_events=False, paths=None):
         for depth, name in enumerate(path, 1):
             if name not in current_tree:
                 current_tree[name] = OrderedDict()
-            if depth == len(path) and ((paths is None and leaf) or (paths is not None and path in paths)):
+            if depth == len(path) and (
+                (paths is None and leaf) or (paths is not None and path in paths)
+            ):
                 # tree measurements have key None, avoiding name conflict
                 if show_events:
                     for event in events: