I signed up for some pay as you go credit - and to my dismay now receive this error both on Disco AND Stable Diffusion:
FileNotFoundError Traceback (most recent call last)
<ipython-input-4-191981527364> in <module>
38 import py3d_tools as p3d
39
---> 40 from helpers import DepthModel, sampler_fn
41 from k_diffusion.external import CompVisDenoiser
42 from ldm.util import instantiate_from_config
4 frames
/content/MiDaS/midas/backbones/next_vit.py in <module>
6 from .utils import activations, forward_default, get_activation
7
----> 8 file = open("./externals/Next_ViT/classification/nextvit.py", "r")
9 source_code = file.read().replace(" utils", " externals.Next_ViT.classification.utils")
10 exec(source_code)
FileNotFoundError: [Errno 2] No such file or directory: './externals/Next_ViT/classification/nextvit.py'
I also receive this error on Stable:
NameError Traceback (most recent call last)
<ipython-input-5-d64464a7a6a5> in <module>
154 if load_on_run_all and ckpt_valid:
155 local_config = OmegaConf.load(f"{ckpt_config_path}")
--> 156 model = load_model_from_config(local_config, f"{ckpt_path}", half_precision=half_precision)
157 device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
158 model = model.to(device)
<ipython-input-5-d64464a7a6a5> in load_model_from_config(config, ckpt, verbose, device, half_precision)
136 print(f"Global Step: {pl_sd['global_step']}")
137 sd = pl_sd["state_dict"]
--> 138 model = instantiate_from_config(config.model)
139 m, u = model.load_state_dict(sd, strict=False)
140 if len(m) > 0 and verbose:
Despite clearing my Google Drive and reloading Disco and Stable Diffusion, (including the .ckpt file, placed correctly as before in the models folder) the same errors occur.
Related
I am running a code on jupyter notebook using virtual machine (Ubuntu). Normally when there is an error it points to the file where the error is giving its path but I got an error with a path I do not have
ValueError Traceback (most recent call last)
/tmp/ipykernel_84/10827517.py in <module>
----> 1 vae_cl.train(max_epochs=500, plan_kwargs=dict(weight_decay=0.0))
/tmp/ipykernel_84/1274271952.py in train(self, max_epochs, n_samples_per_label, check_val_every_n_epoch, train_size, validation_size, batch_size, use_gpu, plan_kwargs, **trainer_kwargs)
187 use_gpu=use_gpu,
188 check_val_every_n_epoch=check_val_every_n_epoch,
--> 189 **trainer_kwargs,
190 )
191 return runner()
/tmp/ipykernel_84/2912366039.py in __init__(self, model, training_plan, data_splitter, max_epochs, use_gpu, **trainer_kwargs)
59 self.data_splitter = data_splitter
60 self.model = model
---> 61 gpus, device = parse_use_gpu_arg(use_gpu)
62 self.gpus = gpus
63 self.device = device
ValueError: too many values to unpack (expected 2)
What I noticed is that the function it is pointing to (---> 61) is actually in the file I am running but I do not understand why the path is like that '/tmp/ipykernel_84/1274271952.py'
Any idea?
I'm working with a previously saved model, however, when I try to load the model, I receive the following error message:
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-11-f8d353bad309> in <module>
----> 1 estimator, corpus_encoder, label_encoder, tokenizer = load_model(MODEL_PATH, loss=weighted_binary_crossentropy)
<ipython-input-6-03f944f0a51f> in load_model(model_base_dir, loss, optimizer, metrics)
9 json_file.close()
10 model = model_from_json(loaded_model_json)
---> 11 model.load_weights(os.path.join(MODEL_PATH, 'model.h5'))
12 model.compile(loss=loss, optimizer=optimizer, metrics=metrics)
13 # loading context_encoder
~\anaconda3\envs\davis_env\lib\site-packages\keras\engine\network.py in load_weights(self, filepath, by_name, skip_mismatch, reshape)
1154 """
1155 if h5py is None:
-> 1156 raise ImportError('`load_weights` requires h5py.')
1157 with h5py.File(filepath, mode='r') as f:
1158 if 'layer_names' not in f.attrs and 'model_weights' in f:
ImportError: `load_weights` requires h5py.
I have since install cython and h5py as described in the answers found here and here
Are there any other solutions?
I'm using tensorflow version 1.12.0 and keras version 2.2.4
UPDATE:
When simply trying to import h5py (via ```import h5py``) I receive the following error message:
ImportError Traceback (most recent call last)
<ipython-input-15-c9f0b8c65221> in <module>
----> 1 import h5py
~\anaconda3\envs\davis_env\lib\site-packages\h5py\__init__.py in <module>
32 raise
33
---> 34 from . import version
35
36 if version.hdf5_version_tuple != version.hdf5_built_version_tuple:
~\anaconda3\envs\davis_env\lib\site-packages\h5py\version.py in <module>
15
16 from collections import namedtuple
---> 17 from . import h5 as _h5
18 import sys
19 import numpy
h5py\h5.pyx in init h5py.h5()
ImportError: DLL load failed: The specified procedure could not be found.```
I'm getting error while preparing List of operators of your serialized torchscript model. What is the issue here? Is it coming when loading it?
Python code
# Dump list of operators used by MobileNetV2:
import torch, yaml
root = '/content/drive/My Drive/Monitoring/'
model = torch.jit.load(root+'model.pt')
ops = torch.jit.export_opnames(model)
with open('MobileNetV2.yaml', 'w') as output:
yaml.dump(ops, output)
Stack Trace
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-39-8b61c35fb898> in <module>()
3
4 root = '/content/drive/My Drive/Monitoring/'
----> 5 model = torch.jit.load(root+'model.pt')
6 ops = torch.jit.export_opnames(model)
7 with open('MobileNetV2.yaml', 'w') as output:
/usr/local/lib/python3.6/dist-packages/torch/jit/_serialization.py in load(f, map_location, _extra_files)
159 cu = torch._C.CompilationUnit()
160 if isinstance(f, str) or isinstance(f, pathlib.Path):
--> 161 cpp_module = torch._C.import_ir_module(cu, f, map_location, _extra_files)
162 else:
163 cpp_module = torch._C.import_ir_module_from_buffer(
RuntimeError: [enforce fail at inline_container.cc:222] . file not found: archive/constants.pkl
I'm trying to train my custom dataset by creating yolov3.cfg file and yolov3.weights file with labelled annotations and images using darkflow. However when I'm trying to run tfnet = TFNet(history), it throws an error of "exit not defined".
I have installed darkflow by the following steps:
In Anaconda Prompt:
git clone https://github.com/thtrieu/darkflow.git
cd darkflow
python3 setup.py build_ext –inplace
pip install
then:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import cv2
from darkflow.net.build import TFNet
history = {"model": "C:/Users/Business Intelli/Desktop/Object-Detection/Dataset/yolov3.cfg",
"load": "C:/Users/Business Intelli/Desktop/Object-Detection/Dataset/yolov3.weights",
"batch": 8,
"epoch": 50,
"gpu": 1.0,
"train": True,
"annotation": "C:/Users/Business Intelli/Desktop/Object-Detection/Dataser/Stumps",
"dataset": "C:/Users/Business Intelli/Desktop/Object-Detection/Dataser/Stumps"}
tfnet = TFNet(history)
Parsing C:/Users/Business Intelli/Desktop/Object-Detection/Dataset/yolov3.cfg
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-10-6f6b945047c5> in <module>
----> 1 tfnet = TFNet(history)
~\Anaconda3\lib\site-packages\darkflow\net\build.py in __init__(self, FLAGS, darknet)
56
57 if darknet is None:
---> 58 darknet = Darknet(FLAGS)
59 self.ntrain = len(darknet.layers)
60
~\Anaconda3\lib\site-packages\darkflow\dark\darknet.py in __init__(self, FLAGS)
15
16 print('Parsing {}'.format(self.src_cfg))
---> 17 src_parsed = self.parse_cfg(self.src_cfg, FLAGS)
18 self.src_meta, self.src_layers = src_parsed
19
~\Anaconda3\lib\site-packages\darkflow\dark\darknet.py in parse_cfg(self, model, FLAGS)
66 cfg_layers = cfg_yielder(*args)
67 meta = dict(); layers = list()
---> 68 for i, info in enumerate(cfg_layers):
69 if i == 0: meta = info; continue
70 else: new = create_darkop(*info)
~\Anaconda3\lib\site-packages\darkflow\utils\process.py in cfg_yielder(model, binary)
314 #-----------------------------------------------------
315 else:
--> 316 exit('Layer {} not
implemented'.format(d['type']))
317
318 d['_size'] = list([h, w, c, l, flat])
NameError: name 'exit' is not defined
So I faced the same problem and the issue is with the process.py file in
darkflow --> utils folder.
Apparently the exit() method is not in-built so you have to add this line in process.py
from sys import exit
Note : If your code is reaching this point it means the models can't read the layers. The weights file that I downloaded for yolov3 gave me same trouble and I couldn't find a link that has a proper weight file for yolov3 that works in darkflow. So I had to stick to yolo.cfg and yolo.weights .
I am trying to replicate the example
Getting Started PyMC3.
on Windows 2012 R2.
The step
from pymc3 import Model, Normal, HalfNormal
gives
D:\Anaconda3\libs/python35.lib: error adding symbols: File in wrong format
collect2.exe: error: ld returned 1 exit status
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
D:\Anaconda3\lib\site-packages\theano\gof\lazylinker_c.py in <module>()
64 if version != getattr(lazylinker_ext, '_version', None):
---> 65 raise ImportError()
66 except ImportError:
ImportError:
During handling of the above exception, another exception occurred:
ImportError Traceback (most recent call last)
D:\Anaconda3\lib\site-packages\theano\gof\lazylinker_c.py in <module>()
81 if version != getattr(lazylinker_ext, '_version', None):
---> 82 raise ImportError()
83 except ImportError:
ImportError:
During handling of the above exception, another exception occurred:
Exception Traceback (most recent call last)
<ipython-input-4-582c90a634a6> in <module>()
----> 1 from pymc3 import Model, Normal, HalfNormal
D:\Anaconda3\lib\site-packages\pymc3\__init__.py in <module>()
1 __version__ = "3.0"
2
----> 3 from .core import *
4 from .distributions import *
5 from .math import *
D:\Anaconda3\lib\site-packages\pymc3\core.py in <module>()
1 from .vartypes import *
----> 2 from .model import *
3 from .theanof import *
4 from .blocking import *
5 import numpy as np
D:\Anaconda3\lib\site-packages\pymc3\model.py in <module>()
1 from .vartypes import *
2
----> 3 from theano import theano, tensor as t, function
4 from theano.tensor.var import TensorVariable
5
D:\Anaconda3\lib\site-packages\theano\__init__.py in <module>()
53 object2, utils
54
---> 55 from theano.compile import \
56 SymbolicInput, In, \
57 SymbolicOutput, Out, \
D:\Anaconda3\lib\site-packages\theano\compile\__init__.py in <module>()
7 SpecifyShape, specify_shape, register_specify_shape_c_code)
8
----> 9 from theano.compile.function_module import *
10
11 from theano.compile.mode import *
D:\Anaconda3\lib\site-packages\theano\compile\function_module.py in <module>()
16 from theano import gof
17 from theano.compat.python2x import partial
---> 18 import theano.compile.mode
19 from theano.compile.io import (
20 In, SymbolicInput, SymbolicInputKit, SymbolicOutput)
D:\Anaconda3\lib\site-packages\theano\compile\mode.py in <module>()
9 import theano
10 from theano import gof
---> 11 import theano.gof.vm
12 from theano.configparser import config, AddConfigVar, StrParam
13 from theano.compile.ops import register_view_op_c_code, _output_guard
D:\Anaconda3\lib\site-packages\theano\gof\vm.py in <module>()
566
567 try:
--> 568 from . import lazylinker_c
569
570 class CVM(lazylinker_c.CLazyLinker, VM):
D:\Anaconda3\lib\site-packages\theano\gof\lazylinker_c.py in <module>()
115 args = cmodule.GCC_compiler.compile_args()
116 cmodule.GCC_compiler.compile_str(dirname, code, location=loc,
--> 117 preargs=args)
118 # Save version into the __init__.py file.
119 init_py = os.path.join(loc, '__init__.py')
D:\Anaconda3\lib\site-packages\theano\gof\cmodule.py in compile_str(module_name, src_code, location, include_dirs, lib_dirs, libs, preargs, py_module)
2008 # difficult to read.
2009 raise Exception('Compilation failed (return status=%s): %s' %
-> 2010 (status, compile_stderr.replace('\n', '. ')))
2011 elif config.cmodule.compilation_warning and compile_stderr:
2012 # Print errors just below the command line.
I have for gcc
C:\>gcc -v
Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=C:/TDM-GCC-64/bin/../libexec/gcc/x86_64-w64-mingw32/5.1.0/lt
o-wrapper.exe
Target: x86_64-w64-mingw32
Configured with: ../../../src/gcc-5.1.0/configure --build=x86_64-w64-mingw32 --e
nable-targets=all --enable-languages=ada,c,c++,fortran,lto,objc,obj-c++ --enable
-libgomp --enable-lto --enable-graphite --enable-cxx-flags=-DWINPTHREAD_STATIC -
-disable-build-with-cxx --disable-build-poststage1-with-cxx --enable-libstdcxx-d
ebug --enable-threads=posix --enable-version-specific-runtime-libs --enable-full
y-dynamic-string --enable-libstdcxx-threads --enable-libstdcxx-time --with-gnu-l
d --disable-werror --disable-nls --disable-win32-registry --prefix=/mingw64tdm -
-with-local-prefix=/mingw64tdm --with-pkgversion=tdm64-1 --with-bugurl=http://td
m-gcc.tdragon.net/bugs
Thread model: posix
gcc version 5.1.0 (tdm64-1)
what am i missing?
thanks
Whatever the issue was creating a python 3.4 environment together with
conda install mingw libpython
solved it.
What solved my issue is installing Python 2.7 version of anaconda
I got the same error using ipython. Using just python I imported theano without problem. Subsequent uses with ipython worked fine after the first compilation with just python.