initial commit
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150
modules/errors.py
Executable file
150
modules/errors.py
Executable file
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import sys
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import textwrap
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import traceback
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exception_records = []
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def format_traceback(tb):
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return [[f"{x.filename}, line {x.lineno}, {x.name}", x.line] for x in traceback.extract_tb(tb)]
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def format_exception(e, tb):
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return {"exception": str(e), "traceback": format_traceback(tb)}
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def get_exceptions():
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try:
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return list(reversed(exception_records))
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except Exception as e:
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return str(e)
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def record_exception():
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_, e, tb = sys.exc_info()
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if e is None:
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return
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if exception_records and exception_records[-1] == e:
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return
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exception_records.append(format_exception(e, tb))
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if len(exception_records) > 5:
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exception_records.pop(0)
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def report(message: str, *, exc_info: bool = False) -> None:
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"""
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Print an error message to stderr, with optional traceback.
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"""
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record_exception()
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for line in message.splitlines():
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print("***", line, file=sys.stderr)
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if exc_info:
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print(textwrap.indent(traceback.format_exc(), " "), file=sys.stderr)
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print("---", file=sys.stderr)
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def print_error_explanation(message):
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record_exception()
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lines = message.strip().split("\n")
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max_len = max([len(x) for x in lines])
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print('=' * max_len, file=sys.stderr)
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for line in lines:
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print(line, file=sys.stderr)
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print('=' * max_len, file=sys.stderr)
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def display(e: Exception, task, *, full_traceback=False):
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record_exception()
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print(f"{task or 'error'}: {type(e).__name__}", file=sys.stderr)
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te = traceback.TracebackException.from_exception(e)
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if full_traceback:
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# include frames leading up to the try-catch block
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te.stack = traceback.StackSummary(traceback.extract_stack()[:-2] + te.stack)
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print(*te.format(), sep="", file=sys.stderr)
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message = str(e)
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if "copying a param with shape torch.Size([640, 1024]) from checkpoint, the shape in current model is torch.Size([640, 768])" in message:
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print_error_explanation("""
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The most likely cause of this is you are trying to load Stable Diffusion 2.0 model without specifying its config file.
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See https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20 for how to solve this.
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""")
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already_displayed = {}
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def display_once(e: Exception, task):
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record_exception()
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if task in already_displayed:
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return
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display(e, task)
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already_displayed[task] = 1
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def run(code, task):
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try:
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code()
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except Exception as e:
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display(task, e)
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def check_versions():
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from packaging import version
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from modules import shared
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import torch
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import gradio
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expected_torch_version = "2.3.1"
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expected_xformers_version = "0.0.27"
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expected_gradio_version = "4.40.0"
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if version.parse(torch.__version__) < version.parse(expected_torch_version):
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print_error_explanation(f"""
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You are running torch {torch.__version__}.
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The program is tested to work with torch {expected_torch_version}.
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To reinstall the desired version, run with commandline flag --reinstall-torch.
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Beware that this will cause a lot of large files to be downloaded, as well as
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there are reports of issues with training tab on the latest version.
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Use --skip-version-check commandline argument to disable this check.
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""".strip())
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if shared.xformers_available:
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import xformers
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if version.parse(xformers.__version__) < version.parse(expected_xformers_version):
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print_error_explanation(f"""
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You are running xformers {xformers.__version__}.
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The program is tested to work with xformers {expected_xformers_version}.
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To reinstall the desired version, run with commandline flag --reinstall-xformers.
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Use --skip-version-check commandline argument to disable this check.
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""".strip())
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if gradio.__version__ != expected_gradio_version:
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print_error_explanation(f"""
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You are running gradio {gradio.__version__}.
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The program is designed to work with gradio {expected_gradio_version}.
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Using a different version of gradio is extremely likely to break the program.
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Reasons why you have the mismatched gradio version can be:
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- you use --skip-install flag.
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- you use webui.py to start the program instead of launch.py.
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- an extension installs the incompatible gradio version.
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Use --skip-version-check commandline argument to disable this check.
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""".strip())
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