Bump tensorflow from 1.13.1 to 2.7.2 in /webapp

megnet/data/graph.py

@@ -192,7 +192,7 @@ def get_flat_data(graphs: list[dict], targets: list | None = None) -> tuple:
         return tuple(output)
 
     @staticmethod
-    def _get_dummy_converter() -> "DummyConverter":
+    def _get_dummy_converter() -> DummyConverter:
         return DummyConverter()
 
     def as_dict(self) -> dict:
@@ -207,7 +207,7 @@ def as_dict(self) -> dict:
         return all_dict
 
     @classmethod
-    def from_dict(cls, d: dict) -> "StructureGraph":
+    def from_dict(cls, d: dict) -> StructureGraph:
         """
         Initialization from dictionary
         Args:
@@ -258,7 +258,7 @@ def convert(self, structure: Structure, state_attributes: list | None = None) ->
         return {"atom": atoms, "bond": bonds, "state": state_attributes, "index1": index1, "index2": index2}
 
     @classmethod
-    def from_structure_graph(cls, structure_graph: StructureGraph) -> "StructureGraphFixedRadius":
+    def from_structure_graph(cls, structure_graph: StructureGraph) -> StructureGraphFixedRadius:
         """
         Initialize from pymatgen StructureGraph
         Args:

megnet/models/base.py

@@ -2,6 +2,7 @@
 Implements basic GraphModels.
 """
 from __future__ import annotations
+
 import os
 from warnings import warn
 
@@ -73,7 +74,7 @@ def train(
         patience: int = 500,
         dirname: str = "callback",
         **kwargs,
-    ) -> "GraphModel":
+    ) -> GraphModel:
         """
         Args:
             train_structures: (list) list of pymatgen structures
@@ -136,7 +137,7 @@ def train_from_graphs(
         save_checkpoint: bool = True,
         dirname: str = "callback",
         **kwargs,
-    ) -> "GraphModel":
+    ) -> GraphModel:
         """
         Args:
             train_graphs: (list) list of graph dictionaries
@@ -375,7 +376,7 @@ def save_model(self, filename: str) -> None:
         )
 
     @classmethod
-    def from_file(cls, filename: str) -> "GraphModel":
+    def from_file(cls, filename: str) -> GraphModel:
         """
         Class method to load model from
             filename for keras model

megnet/models/megnet.py

@@ -2,6 +2,7 @@
 Implements megnet models.
 """
 from __future__ import annotations
+
 from typing import Callable
 
 import numpy as np

megnet/utils/descriptor.py

@@ -3,6 +3,7 @@
 pretrained megnet model
 """
 from __future__ import annotations
+
 import os
 
 import numpy as np

webapp/app.py

@@ -1,13 +1,14 @@
-from flask import Flask, request, render_template, make_response
-from flask.json import jsonify
-from megnet.models import MEGNetModel
-from pymatgen import MPRester, Structure
-import tensorflow as tf
 import glob
 import os
 import re
 from functools import lru_cache
 
+import tensorflow as tf
+from flask import Flask, make_response, render_template, request
+from flask.json import jsonify
+from pymatgen import MPRester, Structure
+
+from megnet.models import MEGNetModel
 
 app = Flask(__name__)
 mpr = MPRester(os.environ.get("MAPI_KEY"))
@@ -36,7 +37,7 @@ def predict(model_name, structure):
         model = models[model_name]
         with graph.as_default():
             return model.predict_structure(structure).ravel()
-    except Exception as ex:
+    except Exception:
         return float("nan")
 
 
@@ -52,10 +53,18 @@ def get_results(structure):
 
 @lru_cache(maxsize=64)
 def get_mp_results(mp_id):
-    data = mpr.query({"task_id": mp_id},
-                     properties=["structure", "formation_energy_per_atom",
-                                 "band_gap", "efermi", "elasticity.K_VRH", "elasticity.G_VRH"],
-                     mp_decode=False)
+    data = mpr.query(
+        {"task_id": mp_id},
+        properties=[
+            "structure",
+            "formation_energy_per_atom",
+            "band_gap",
+            "efermi",
+            "elasticity.K_VRH",
+            "elasticity.G_VRH",
+        ],
+        mp_decode=False,
+    )
     data = data[0]
     s = Structure.from_dict(data["structure"])
     formula = s.composition.reduced_formula
@@ -68,36 +77,32 @@ def get_mp_results(mp_id):
     return formula, results
 
 
-@app.route('/')
+@app.route("/")
 def index():
-    return make_response(render_template('index.html'))
+    return make_response(render_template("index.html"))
 
 
-@app.route('/models')
+@app.route("/models")
 def get_models():
     return jsonify(list(models.keys()))
 
 
-@app.route('/query', methods=['GET'])
+@app.route("/query", methods=["GET"])
 def query():
     message = ""
     try:
         mp_id = request.args.get("mp_id")
         formula, results = get_mp_results(mp_id)
-    except Exception as ex:
+    except Exception:
         message = "Please check your Materials Project Id."
         formula = ""
         results = []
-    return make_response(render_template(
-        'index.html',
-        mp_id=mp_id,
-        formula=html_formula(formula),
-        message=message,
-        mp_results=results
-    ))
+    return make_response(
+        render_template("index.html", mp_id=mp_id, formula=html_formula(formula), message=message, mp_results=results)
+    )
 
 
-@app.route('/query_structure', methods=['POST'])
+@app.route("/query_structure", methods=["POST"])
 def query_structure():
     formula = ""
     message = ""
@@ -116,58 +121,50 @@ def query_structure():
         results = get_results(s)
     except Exception as ex:
         message = "Error reading structure! %s" % (str(ex))
-    return make_response(render_template(
-        'index.html',
-        structure_string=structure_string,
-        formula=html_formula(formula),
-        structure_results=results,
-        message=message
-    ))
-
-
-@app.route('/rest/predict_structure/<string:model_name>', methods=['POST'])
+    return make_response(
+        render_template(
+            "index.html",
+            structure_string=structure_string,
+            formula=html_formula(formula),
+            structure_results=results,
+            message=message,
+        )
+    )
+
+
+@app.route("/rest/predict_structure/<string:model_name>", methods=["POST"])
 def predict_structure_rest(model_name):
     try:
-        structure = Structure.from_str(request.form["structure"],
-            fmt=request.form["fmt"])
+        structure = Structure.from_str(request.form["structure"], fmt=request.form["fmt"])
         val = predict(model_name, structure)
-        d = {
-            "model": model_name,
-            "val": float(val),
-            "formula": structure.composition.reduced_formula
-        }
+        d = {"model": model_name, "val": float(val), "formula": structure.composition.reduced_formula}
         return jsonify(d)
     except Exception as ex:
         return jsonify(str(ex))
 
 
-@app.route('/rest/predict_mp/<string:model_name>/<string:mp_id>')
+@app.route("/rest/predict_mp/<string:model_name>/<string:mp_id>")
 def predict_mp_rest(model_name, mp_id):
     try:
         structure = mpr.get_structure_by_material_id(mp_id)
         val = predict(model_name, structure)
-        d = {
-            "model": model_name,
-            "val": float(val),
-            "formula": structure.composition.reduced_formula
-        }
+        d = {"model": model_name, "val": float(val), "formula": structure.composition.reduced_formula}
         return jsonify(d)
     except Exception as ex:
         return jsonify(str(ex))
 
 
-@app.route('/predict_structure/<string:model_name>', methods=['POST'])
+@app.route("/predict_structure/<string:model_name>", methods=["POST"])
 def predict_structure(model_name):
     try:
-        structure = Structure.from_str(request.form["structure"], 
-            fmt=request.form["fmt"])
+        structure = Structure.from_str(request.form["structure"], fmt=request.form["fmt"])
         val = predict(model_name, structure)
         return jsonify(float(val))
     except Exception as ex:
         return jsonify(str(ex))
 
 
-@app.route('/predict_mp/<string:model_name>/<string:mp_id>')
+@app.route("/predict_mp/<string:model_name>/<string:mp_id>")
 def predict_mp(model_name, mp_id):
     try:
         structure = mpr.get_structure_by_material_id(mp_id)
@@ -182,20 +179,28 @@ def main():
     import argparse
 
     parser = argparse.ArgumentParser(
-        description="""Basic web app for MEGNet.""",
-        epilog="Authors: Chi Chen, Shyue Ping Ong")
+        description="""Basic web app for MEGNet.""", epilog="Authors: Chi Chen, Shyue Ping Ong"
+    )
 
+    parser.add_argument("-d", "--debug", dest="debug", action="store_true", help="Whether to run in debug mode.")
     parser.add_argument(
-        "-d", "--debug", dest="debug", action="store_true",
-        help="Whether to run in debug mode.")
-    parser.add_argument(
-        "-hh", "--host", dest="host", type=str, nargs="?",
-        default='0.0.0.0',
-        help="Host in which to run the server. Defaults to 0.0.0.0.")
+        "-hh",
+        "--host",
+        dest="host",
+        type=str,
+        nargs="?",
+        default="0.0.0.0",
+        help="Host in which to run the server. Defaults to 0.0.0.0.",
+    )
     parser.add_argument(
-        "-p", "--port", dest="port", type=int, nargs="?",
+        "-p",
+        "--port",
+        dest="port",
+        type=int,
+        nargs="?",
         default=5000,
-        help="Port in which to run the server. Defaults to 5000.")
+        help="Port in which to run the server. Defaults to 5000.",
+    )
 
     args = parser.parse_args()
     init()

webapp/requirements.txt

@@ -1,5 +1,5 @@
 pymatgen==2019.7.30
-tensorflow==1.13.1
+tensorflow==2.7.2
 keras==2.2.4
 megnet==0.3.5
 gunicorn==19.9.0

webapp/static/index.css

@@ -13,7 +13,7 @@
 
 #profile{
     text-align: center;
-    font-size: 1.5em;   
+    font-size: 1.5em;
 }
 
 input{
@@ -59,4 +59,4 @@ table {
 textarea{
     font-size: 0.8em;
     margin: auto;
-}
+}

webapp/static/style.css

@@ -107,4 +107,4 @@ h1, h2 {
 .tagline {
     font-size: 1.2em;
     text-align: center;
-}
+}