144 lines
4.4 KiB
Python
144 lines
4.4 KiB
Python
import numpy as np
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import os
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import shutil
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from html.parser import HTMLParser
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import onnx
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import logging
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import re
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if onnx.__version__ == '1.7.0':
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extract_bie_ioinfo = lambda x: ([], []) # Dummy function for onnx 1.7.0
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else:
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from extract_bie_info import extract_bie_ioinfo
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RESULT_FOLDER = "/data1/kneron_flow"
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TMP_FOLDER = "/workspace/.tmp"
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LIBS_V1_FOLDER = "/workspace/libs"
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LIBS_V2_FOLDER = "/workspace/libs_V2"
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SCRIPT_FOLDER = "/workspace/scripts"
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def convert_channel_last_to_first(image):
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"""Convert channel last input image to channel first.
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WARNING: This function is only valid for 2D image input.
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Args:
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image (np.array): input image
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Returns:
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np.array: converted input image
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"""
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# Check if the input image is a numpy array. If not, create a numpy array
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if not isinstance(image, np.ndarray):
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image = np.array(image)
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# Check if the input is 4D. If not, unsqueeze the input image.
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if len(image.shape) == 3:
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image = np.expand_dims(image, axis=0)
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return np.moveaxis(image, -1, 1)
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def get_toolchain_version():
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f = None
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try:
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f = open("/workspace/version.txt", "r")
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result = f.read()
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except:
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result = "Unknown"
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finally:
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if f:
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f.close()
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return result
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def clean_up(output_dir, files_to_delete=None, dirs_to_delete=None):
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files_to_delete = files_to_delete or []
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dirs_to_delete = dirs_to_delete or []
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for file in files_to_delete:
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abs_path = os.path.join(output_dir, file)
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if os.path.isfile(abs_path):
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os.remove(abs_path)
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for folder in dirs_to_delete:
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abs_path = os.path.join(output_dir, folder)
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if os.path.isdir(abs_path):
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shutil.rmtree(abs_path)
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def evalutor_result_html_parse(html_content):
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"""Print the html content in the result.html file."""
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# Convert HTML table to dictionary
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class EvaluatorHTMLParser(HTMLParser):
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def __init__(self):
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HTMLParser.__init__(self)
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self.result = ""
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# Status: 0 for not started, 1 for info table, 2 for details table
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self.status = 0
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def handle_starttag(self, tag, attrs):
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if self.status == 0 and tag == "tbody" and len(self.result) == 0:
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self.status = 1
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if self.status == 0 and tag == "thead" and len(self.result) > 0:
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self.status = 2
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def handle_endtag(self, tag):
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if self.status == 0:
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pass
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elif tag == "tr":
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self.result += "\n"
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elif self.status == 1 and tag == "tbody":
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self.status = 0
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self.result += "\n"
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elif self.status == 1 and tag == "th":
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self.result += ": "
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elif self.status == 2 and tag in ["th", "td"]:
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self.result += ", "
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def handle_data(self, data):
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if self.status != 0:
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self.result += data.strip()
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parser = EvaluatorHTMLParser()
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parser.feed(html_content)
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parser.close()
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return parser.result
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def get_input_names_from_onnx(onnx_model):
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"""Get input names from onnx model."""
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if onnx_model is None:
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logging.error("onnx_model is None.")
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return []
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if not isinstance(onnx_model, onnx.ModelProto):
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logging.error("onnx_model should be an instance of onnx.ModelProto.")
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return []
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input_names = [input.name for input in onnx_model.graph.input]
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return input_names
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def get_input_names_from_bie(bie_path):
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"""Get input names from bie file."""
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if bie_path is None:
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logging.error("bie_path is None.")
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return []
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if not os.path.isfile(bie_path):
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logging.error(f"bie file {bie_path} does not exist.")
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return []
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input_names, _ = extract_bie_ioinfo(bie_path)
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return input_names
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def check_filename_validity(filename):
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"""Check if the filename is valid."""
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if not isinstance(filename, str):
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logging.error("Filename should be a string.")
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return False
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if not filename:
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logging.error("Filename should not be empty.")
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return False
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filename = os.path.basename(filename)
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filename = os.path.splitext(filename)[0]
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if not re.match(r'^[\w.-]+$', filename):
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logging.warning(f"Invalid filename: {filename}. Only alphanumeric characters, underscores, hyphens, and dots are allowed.")
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return False
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return True
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