Updated setup.py and removed outdated TODO

hpvm/projects/torch2hpvm/TODO.md

-# What kind of models we should use
-ResNet-50 -> as a start?
-BERT
-Mask R-CNN
-
-# Questions from Sudipta
-Graph optimization: operator fusions, data layout transformations
-Vectorization/tensorization
-Automatic scheduling
-Handling dynamic control flow in model graph
-Automatic differentiation
-
-# Operators used in the BERT model available in the ONNX model zoo, organized by type and number of occurences
-
-https://github.com/onnx/models/tree/master/text/machine_comprehension/bert-squad
-(Opset 10 versions)
-
-DATA MANIPULATION
-Unsqueeze 191
-Reshape 71
-Cast 70
-Transpose 62
-Concat 56
-Identity 28
-Squeeze 7
-Slice
-Shape 5
-ConstantOfShape 1
-Gather 1
-OneHot 1
-Split 1
-
-COMPUTATION
-Mul 186
-Add 185
-MatMul 98
-Sub 62
-ReduceMean 50
-Sqrt 25
-Reciprocal 25
-Softmax 12
-Pow 12
-Tanh 12

hpvm/projects/torch2hpvm/setup.py

@@ -4,11 +4,14 @@ setup(
     name="torch2hpvm",
     version="1.0",
     description="PyTorch frontend for HPVM",
-    author="Yuanjing Shi, Yifan Zhao",
-    author_email="ys26@illinois.edu, yifanz16@illinois.edu",
+    author="Yifan Zhao, Yuanjing Shi",
+    author_email="yifanz16@illinois.edu, ys26@illinois.edu",
     packages=["torch2hpvm"],
     install_requires=[
-        "jinja2>=2.11", "networkx>=2.5", "onnx>=1.8.0", "torch", "onnx-simplifier>=0.2.27"
+        "jinja2>=2.11",
+        "networkx>=2.5",
+        "onnx>=1.8.0",
+        "torch>=1.5",
+        "onnx-simplifier>=0.2.27",
     ],
-    entry_points={"console_scripts": ["torch2hpvm=torch2hpvm:main"]},
 )