mirror of
https://github.com/The-OpenROAD-Project/OpenLane.git
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7a65b61b17
+ Added linting rules for flake8, formatting with black + Added a GitHub Action to enforce lint/format rules
84 lines
2.6 KiB
Python
84 lines
2.6 KiB
Python
#!/usr/bin/python3
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# Copyright 2020 Efabless Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import pandas as pd
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import re
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def get_design_path(design):
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path = os.path.abspath(design) + "/"
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if not os.path.exists(path):
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path = os.path.join(os.getcwd(), "./designs/{design}/".format(design=design))
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if os.path.exists(path):
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return path
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else:
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return None
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def get_run_path(design, tag):
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return os.path.join(get_design_path(design), "runs", tag)
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def get_design_name(design, config):
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design_path = get_design_path(design=design)
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if design_path is None:
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return ("Design path not found", None)
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config_file = "{design_path}/{config}.tcl".format(
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design_path=design_path,
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config=config,
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)
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try:
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config_file_opener = open(config_file, "r")
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configs = config_file_opener.read()
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config_file_opener.close()
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pattern = re.compile(r"\s*?set ::env\(DESIGN_NAME\)\s*?(\S+)\s*")
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for name in re.findall(pattern, configs):
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return (None, name.strip('"{}'))
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return ("Invalid configuration file", None)
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except OSError:
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return ("Configuration file not found", None)
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# add_computed_statistics adds: CellPerMMSquaredOverCoreUtil, suggested_clock_period, and suggested_clock_frequency to a report.csv
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def add_computed_statistics(filename):
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data = pd.read_csv(filename)
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df = pd.DataFrame(data)
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diearea_mm2_index = df.columns.get_loc("DIEAREA_mm^2")
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df.insert(
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diearea_mm2_index,
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column="(Cell/mm^2)/Core_Util",
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value=df["CellPer_mm^2"] / (df["FP_CORE_UTIL"] / 100),
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allow_duplicates=True,
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)
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suggest_clock_period = df["CLOCK_PERIOD"] - df["spef_wns"]
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clock_period_index = df.columns.get_loc("CLOCK_PERIOD")
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df.insert(
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clock_period_index,
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column="suggested_clock_period",
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value=suggest_clock_period,
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allow_duplicates=True,
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)
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df.insert(
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clock_period_index,
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column="suggested_clock_frequency",
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value=1000.0 / suggest_clock_period,
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allow_duplicates=True,
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)
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df.to_csv(filename)
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