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The dataset generation failed
Error code: DatasetGenerationError
Exception: UnicodeDecodeError
Message: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 609, in wrapped
for item in generator(*args, **kwargs):
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/text/text.py", line 81, in _generate_tables
batch = f.read(self.config.chunksize)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 844, in read_with_retries
out = read(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "<frozen codecs>", line 322, in decode
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1342, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 907, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1919, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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from typing_extensions import override |
from comfy_api.latest import ComfyExtension, io |
class Example(io.ComfyNode): |
""" |
An example node |
Class methods |
------------- |
define_schema (io.Schema): |
Tell the main program the metadata, input, output parameters of nodes. |
fingerprint_inputs: |
optional method to control when the node is re executed. |
check_lazy_status: |
optional method to control list of input names that need to be evaluated. |
""" |
@classmethod |
def define_schema(cls) -> io.Schema: |
""" |
Return a schema which contains all information about the node. |
Some types: "Model", "Vae", "Clip", "Conditioning", "Latent", "Image", "Int", "String", "Float", "Combo". |
For outputs the "io.Model.Output" should be used, for inputs the "io.Model.Input" can be used. |
The type can be a "Combo" - this will be a list for selection. |
""" |
return io.Schema( |
node_id="Example", |
display_name="Example Node", |
category="Example", |
inputs=[ |
io.Image.Input("image"), |
io.Int.Input( |
"int_field", |
min=0, |
max=4096, |
step=64, # Slider's step |
display_mode=io.NumberDisplay.number, # Cosmetic only: display as "number" or "slider" |
lazy=True, # Will only be evaluated if check_lazy_status requires it |
), |
io.Float.Input( |
"float_field", |
default=1.0, |
min=0.0, |
max=10.0, |
step=0.01, |
round=0.001, #The value representing the precision to round to, will be set to the step value by default. Can be set to False to disable rounding. |
display_mode=io.NumberDisplay.number, |
lazy=True, |
), |
io.Combo.Input("print_to_screen", options=["enable", "disable"]), |
io.String.Input( |
"string_field", |
multiline=False, # True if you want the field to look like the one on the ClipTextEncode node |
default="Hello world!", |
lazy=True, |
) |
], |
outputs=[ |
io.Image.Output(), |
], |
) |
@classmethod |
def check_lazy_status(cls, image, string_field, int_field, float_field, print_to_screen): |
""" |
Return a list of input names that need to be evaluated. |
This function will be called if there are any lazy inputs which have not yet been |
evaluated. As long as you return at least one field which has not yet been evaluated |
(and more exist), this function will be called again once the value of the requested |
field is available. |
Any evaluated inputs will be passed as arguments to this function. Any unevaluated |
inputs will have the value None. |
""" |
if print_to_screen == "enable": |
return ["int_field", "float_field", "string_field"] |
else: |
return [] |
@classmethod |
def execute(cls, image, string_field, int_field, float_field, print_to_screen) -> io.NodeOutput: |
if print_to_screen == "enable": |
print(f"""Your input contains: |
string_field aka input text: {string_field} |
int_field: {int_field} |
float_field: {float_field} |
""") |
#do some processing on the image, in this example I just invert it |
image = 1.0 - image |
return io.NodeOutput(image) |
""" |
The node will always be re executed if any of the inputs change but |
this method can be used to force the node to execute again even when the inputs don't change. |
You can make this node return a number or a string. This value will be compared to the one returned the last time the node was |
executed, if it is different the node will be executed again. |
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