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import sys
import textwrap
import traceback
exception_records = []
def format_traceback(tb):
return [[f"{x.filename}, line {x.lineno}, {x.name}", x.line] for x in traceback.extract_tb(tb)]
def format_exception(e, tb):
return {"exception": str(e), "traceback": format_traceback(tb)}
def get_exceptions():
try:
return list(reversed(exception_records))
except Exception as e:
return str(e)
def record_exception():
_, e, tb = sys.exc_info()
if e is None:
return
if exception_records and exception_records[-1] == e:
return
exception_records.append(format_exception(e, tb))
if len(exception_records) > 5:
exception_records.pop(0)
def report(message: str, *, exc_info: bool = False) -> None:
"""
Print an error message to stderr, with optional traceback.
"""
record_exception()
for line in message.splitlines():
print("***", line, file=sys.stderr)
if exc_info:
print(textwrap.indent(traceback.format_exc(), " "), file=sys.stderr)
print("---", file=sys.stderr)
def print_error_explanation(message):
record_exception()
lines = message.strip().split("\n")
max_len = max([len(x) for x in lines])
print('=' * max_len, file=sys.stderr)
for line in lines:
print(line, file=sys.stderr)
print('=' * max_len, file=sys.stderr)
def display(e: Exception, task, *, full_traceback=False):
record_exception()
print(f"{task or 'error'}: {type(e).__name__}", file=sys.stderr)
te = traceback.TracebackException.from_exception(e)
if full_traceback:
# include frames leading up to the try-catch block
te.stack = traceback.StackSummary(traceback.extract_stack()[:-2] + te.stack)
print(*te.format(), sep="", file=sys.stderr)
message = str(e)
if "copying a param with shape torch.Size([640, 1024]) from checkpoint, the shape in current model is torch.Size([640, 768])" in message:
print_error_explanation("""
The most likely cause of this is you are trying to load Stable Diffusion 2.0 model without specifying its config file.
See https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20 for how to solve this.
""")
already_displayed = {}
def display_once(e: Exception, task):
record_exception()
if task in already_displayed:
return
display(e, task)
already_displayed[task] = 1
def run(code, task):
try:
code()
except Exception as e:
display(task, e)
def check_versions():
from packaging import version
from modules import shared
import torch
import gradio
expected_torch_version = "2.1.2"
expected_xformers_version = "0.0.23.post1"
expected_gradio_version = "3.41.2"
if version.parse(torch.__version__) < version.parse(expected_torch_version):
print_error_explanation(f"""
You are running torch {torch.__version__}.
The program is tested to work with torch {expected_torch_version}.
To reinstall the desired version, run with commandline flag --reinstall-torch.
Beware that this will cause a lot of large files to be downloaded, as well as
there are reports of issues with training tab on the latest version.
Use --skip-version-check commandline argument to disable this check.
""".strip())
if shared.xformers_available:
import xformers
if version.parse(xformers.__version__) < version.parse(expected_xformers_version):
print_error_explanation(f"""
You are running xformers {xformers.__version__}.
The program is tested to work with xformers {expected_xformers_version}.
To reinstall the desired version, run with commandline flag --reinstall-xformers.
Use --skip-version-check commandline argument to disable this check.
""".strip())
if gradio.__version__ != expected_gradio_version:
print_error_explanation(f"""
You are running gradio {gradio.__version__}.
The program is designed to work with gradio {expected_gradio_version}.
Using a different version of gradio is extremely likely to break the program.
Reasons why you have the mismatched gradio version can be:
- you use --skip-install flag.
- you use webui.py to start the program instead of launch.py.
- an extension installs the incompatible gradio version.
Use --skip-version-check commandline argument to disable this check.
""".strip())
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