object of type 'NoneType' has no len()
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sadath-12 commented
With this provided training script
from datetime import datetime
import torch.utils.data
from torch import optim
from minimagen.Imagen import Imagen
from minimagen.Unet import Unet, Base, Super, BaseTest, SuperTest
from minimagen.generate import load_minimagen, load_params
from minimagen.t5 import get_encoded_dim
from minimagen.training import get_minimagen_parser, ConceptualCaptions, get_minimagen_dl_opts, \
create_directory, get_model_params, get_model_size, save_training_info, get_default_args, MinimagenTrain, \
load_restart_training_parameters, load_testing_parameters
# Get device
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
# Command line argument parser
parser = get_minimagen_parser()
# args = parser.parse_args()
args = parser.parse_known_args()
# Create training directory
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
dir_path = f"./training_{timestamp}"
training_dir = create_directory(dir_path)
# Replace some cmd line args to lower computational load.
args = load_testing_parameters(args)
# Load subset of Conceptual Captions dataset.
train_dataset, valid_dataset = ConceptualCaptions(args, smalldata=True)
# Create dataloaders
dl_opts = {**get_minimagen_dl_opts(device), 'batch_size': args.BATCH_SIZE, 'num_workers': args.NUM_WORKERS}
train_dataloader = torch.utils.data.DataLoader(train_dataset, **dl_opts)
valid_dataloader = torch.utils.data.DataLoader(valid_dataset, **dl_opts)
# Use small U-Nets to lower computational load.
unets_params = [get_default_args(BaseTest), get_default_args(SuperTest)]
unets = [Unet(**unet_params).to(device) for unet_params in unets_params]
# Specify MinImagen parameters
imagen_params = dict(
image_sizes=(int(args.IMG_SIDE_LEN / 2), args.IMG_SIDE_LEN),
timesteps=args.TIMESTEPS,
cond_drop_prob=0.15,
text_encoder_name=args.T5_NAME
)
# Create MinImagen from UNets with specified imagen parameters
imagen = Imagen(unets=unets, **imagen_params).to(device)
# Fill in unspecified arguments with defaults to record complete config (parameters) file
unets_params = [{**get_default_args(Unet), **i} for i in unets_params]
imagen_params = {**get_default_args(Imagen), **imagen_params}
# Get the size of the Imagen model in megabytes
model_size_MB = get_model_size(imagen)
# Save all training info (config files, model size, etc.)
save_training_info(args, timestamp, unets_params, imagen_params, model_size_MB, training_dir)
# Create optimizer
optimizer = optim.Adam(imagen.parameters(), lr=args.OPTIM_LR)
# Train the MinImagen instance
MinimagenTrain(timestamp, args, unets, imagen, train_dataloader, valid_dataloader, training_dir, optimizer, timeout=30)
from argparse import ArgumentParser
from minimagen.generate import load_minimagen, sample_and_save
# Command line argument parser
parser = ArgumentParser()
parser.add_argument("-d", "--TRAINING_DIRECTORY", dest="TRAINING_DIRECTORY", help="Training directory to use for inference", type=str)
args = parser.parse_args()
# Specify the caption(s) to generate images for
captions = ['a happy dog']
# Use `sample_and_save` to generate and save the iamges
sample_and_save(captions, training_directory=args.TRAINING_DIRECTORY)
# Alternatively, rather than specifying a Training Directory, you can input just a MinImagen instance to use for image generation.
# In this case, information about the MinImagen instance used to generate the images will not be saved.
minimagen = load_minimagen(args.TRAINING_DIRECTORY)
sample_and_save(captions, minimagen=minimagen) ```
I get error ``` usage: ipykernel_launcher.py [-h] [-p PARAMETERS] [-n NUM_WORKERS]
[-b BATCH_SIZE] [-mw MAX_NUM_WORDS]
[-s IMG_SIDE_LEN] [-e EPOCHS] [-t5 T5_NAME]
[-f TRAIN_VALID_FRAC] [-t TIMESTEPS]
[-lr OPTIM_LR] [-ai ACCUM_ITER] [-cn CHCKPT_NUM]
[-vn VALID_NUM] [-rd RESTART_DIRECTORY] [-test]
ipykernel_launcher.py: error: argument -f/--TRAIN_VALID_FRAC: invalid float value: '/root/.local/share/jupyter/runtime/kernel-7d986ed8-b1e3-4cc4-b594-d8d9901e471a.json'
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
File /opt/conda/lib/python3.10/argparse.py:2488, in ArgumentParser._get_value(self, action, arg_string)
2487 try:
-> 2488 result = type_func(arg_string)
2490 # ArgumentTypeErrors indicate errors
ValueError: could not convert string to float: '/root/.local/share/jupyter/runtime/kernel-7d986ed8-b1e3-4cc4-b594-d8d9901e471a.json'
During handling of the above exception, another exception occurred:
ArgumentError Traceback (most recent call last)
File /opt/conda/lib/python3.10/argparse.py:1859, in ArgumentParser.parse_known_args(self, args, namespace)
1858 try:
-> 1859 namespace, args = self._parse_known_args(args, namespace)
1860 except ArgumentError:
File /opt/conda/lib/python3.10/argparse.py:2072, in ArgumentParser._parse_known_args(self, arg_strings, namespace)
2071 # consume the next optional and any arguments for it
-> 2072 start_index = consume_optional(start_index)
2074 # consume any positionals following the last Optional
File /opt/conda/lib/python3.10/argparse.py:2012, in ArgumentParser._parse_known_args.<locals>.consume_optional(start_index)
2011 for action, args, option_string in action_tuples:
-> 2012 take_action(action, args, option_string)
2013 return stop
File /opt/conda/lib/python3.10/argparse.py:1920, in ArgumentParser._parse_known_args.<locals>.take_action(action, argument_strings, option_string)
1919 seen_actions.add(action)
-> 1920 argument_values = self._get_values(action, argument_strings)
1922 # error if this argument is not allowed with other previously
1923 # seen arguments, assuming that actions that use the default
1924 # value don't really count as "present"
File /opt/conda/lib/python3.10/argparse.py:2455, in ArgumentParser._get_values(self, action, arg_strings)
2454 arg_string, = arg_strings
-> 2455 value = self._get_value(action, arg_string)
2456 self._check_value(action, value)
File /opt/conda/lib/python3.10/argparse.py:2501, in ArgumentParser._get_value(self, action, arg_string)
2500 msg = _('invalid %(type)s value: %(value)r')
-> 2501 raise ArgumentError(action, msg % args)
2503 # return the converted value
ArgumentError: argument -f/--TRAIN_VALID_FRAC: invalid float value: '/root/.local/share/jupyter/runtime/kernel-7d986ed8-b1e3-4cc4-b594-d8d9901e471a.json'
During handling of the above exception, another exception occurred:
SystemExit Traceback (most recent call last)
[... skipping hidden 1 frame]
Cell In[4], line 21
20 # args = parser.parse_args()
---> 21 args = parser.parse_known_args()
22 args=args[0]
File /opt/conda/lib/python3.10/argparse.py:1862, in ArgumentParser.parse_known_args(self, args, namespace)
1861 err = _sys.exc_info()[1]
-> 1862 self.error(str(err))
1863 else:
File /opt/conda/lib/python3.10/argparse.py:2587, in ArgumentParser.error(self, message)
2586 args = {'prog': self.prog, 'message': message}
-> 2587 self.exit(2, _('%(prog)s: error: %(message)s\n') % args)
File /opt/conda/lib/python3.10/argparse.py:2574, in ArgumentParser.exit(self, status, message)
2573 self._print_message(message, _sys.stderr)
-> 2574 _sys.exit(status)
SystemExit: 2
During handling of the above exception, another exception occurred:
AttributeError Traceback (most recent call last)
[... skipping hidden 1 frame]
File /opt/conda/lib/python3.10/site-packages/IPython/core/interactiveshell.py:2095, in InteractiveShell.showtraceback(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)
2092 if exception_only:
2093 stb = ['An exception has occurred, use %tb to see '
2094 'the full traceback.\n']
-> 2095 stb.extend(self.InteractiveTB.get_exception_only(etype,
2096 value))
2097 else:
2098 try:
2099 # Exception classes can customise their traceback - we
2100 # use this in IPython.parallel for exceptions occurring
2101 # in the engines. This should return a list of strings.
File /opt/conda/lib/python3.10/site-packages/IPython/core/ultratb.py:696, in ListTB.get_exception_only(self, etype, value)
688 def get_exception_only(self, etype, value):
689 """Only print the exception type and message, without a traceback.
690
691 Parameters
(...)
694 value : exception value
695 """
--> 696 return ListTB.structured_traceback(self, etype, value)
File /opt/conda/lib/python3.10/site-packages/IPython/core/ultratb.py:559, in ListTB.structured_traceback(self, etype, evalue, etb, tb_offset, context)
556 chained_exc_ids.add(id(exception[1]))
557 chained_exceptions_tb_offset = 0
558 out_list = (
--> 559 self.structured_traceback(
560 etype,
561 evalue,
562 (etb, chained_exc_ids), # type: ignore
563 chained_exceptions_tb_offset,
564 context,
565 )
566 + chained_exception_message
567 + out_list)
569 return out_list
File /opt/conda/lib/python3.10/site-packages/IPython/core/ultratb.py:1396, in AutoFormattedTB.structured_traceback(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)
1394 else:
1395 self.tb = etb
-> 1396 return FormattedTB.structured_traceback(
1397 self, etype, evalue, etb, tb_offset, number_of_lines_of_context
1398 )
File /opt/conda/lib/python3.10/site-packages/IPython/core/ultratb.py:1287, in FormattedTB.structured_traceback(self, etype, value, tb, tb_offset, number_of_lines_of_context)
1284 mode = self.mode
1285 if mode in self.verbose_modes:
1286 # Verbose modes need a full traceback
-> 1287 return VerboseTB.structured_traceback(
1288 self, etype, value, tb, tb_offset, number_of_lines_of_context
1289 )
1290 elif mode == 'Minimal':
1291 return ListTB.get_exception_only(self, etype, value)
File /opt/conda/lib/python3.10/site-packages/IPython/core/ultratb.py:1140, in VerboseTB.structured_traceback(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)
1131 def structured_traceback(
1132 self,
1133 etype: type,
(...)
1137 number_of_lines_of_context: int = 5,
1138 ):
1139 """Return a nice text document describing the traceback."""
-> 1140 formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,
1141 tb_offset)
1143 colors = self.Colors # just a shorthand + quicker name lookup
1144 colorsnormal = colors.Normal # used a lot
File /opt/conda/lib/python3.10/site-packages/IPython/core/ultratb.py:1030, in VerboseTB.format_exception_as_a_whole(self, etype, evalue, etb, number_of_lines_of_context, tb_offset)
1027 assert isinstance(tb_offset, int)
1028 head = self.prepare_header(str(etype), self.long_header)
1029 records = (
-> 1030 self.get_records(etb, number_of_lines_of_context, tb_offset) if etb else []
1031 )
1033 frames = []
1034 skipped = 0
File /opt/conda/lib/python3.10/site-packages/IPython/core/ultratb.py:1098, in VerboseTB.get_records(self, etb, number_of_lines_of_context, tb_offset)
1096 while cf is not None:
1097 try:
-> 1098 mod = inspect.getmodule(cf.tb_frame)
1099 if mod is not None:
1100 mod_name = mod.__name__
AttributeError: 'tuple' object has no attribute 'tb_frame' ```
To Reproduce the same error Run the following script in google collab or kaggle sadath-12 commented
solved**