Unsupported Image type about ffcv HOT 6 CLOSED

import numpy as np

from ffcv.writer import DatasetWriter
from ffcv.fields import BytesField
from ffcv.loader import Loader

ENC = "utf-8"
DATA_PATH = "data.beton"


def encode(s: str):
    return np.frombuffer(s.encode(ENC), dtype="uint8")


data = [(encode("hello"),), (encode("world!!"),), (encode("how is life"),)]

writer = DatasetWriter(DATA_PATH, {"text": BytesField()})
writer.from_indexed_dataset(data)

loader = Loader(DATA_PATH, batch_size=1)

for item in loader:
    print("raw out\t", item)
    print("decoded\t", item[0].numpy().tobytes().decode(ENC))

import numpy as np
from uuid import uuid4
from ffcv.writer import DatasetWriter
from ffcv.fields import NDArrayField
from ffcv.loader import Loader, OrderOption
from ffcv.fields.decoders import NDArrayDecoder
from tempfile import NamedTemporaryFile

MAX_STRING_SIZE = 100

class CaptionDataset:
    def __init__(self, N):
        self.captions = [str(uuid4())[:np.random.randint(50)] for _ in range(N)]

    def __getitem__(self, idx):
        padded_caption = (self.captions[idx] + (" " * MAX_STRING_SIZE))[:MAX_STRING_SIZE]
        return (np.frombuffer(padded_caption.encode('ascii'), dtype='uint8'),)

    def __len__(self):
        return len(self.captions)

dataset = CaptionDataset(100)

with NamedTemporaryFile() as handle:
    writer = DatasetWriter(handle.name, {
        'label': NDArrayField(np.dtype('uint8'), (MAX_STRING_SIZE,))
    }, num_workers=1)

    writer.from_indexed_dataset(dataset)

    loader = Loader(handle.name,
                batch_size=10,
                num_workers=2,
                order=OrderOption.RANDOM,
                pipelines={
                    'label': [NDArrayDecoder()]
                })

    for x, in loader:
        for cap in x:
            print(cap.tobytes().decode('ascii').strip())

import numpy as np

from ffcv.writer import DatasetWriter
from ffcv.fields import JSONField
from ffcv.loader import Loader

ENC = "utf-8"
DATA_PATH = "data.beton"


def encode(s: str):
    return np.frombuffer(s.encode(ENC), dtype="uint8")


data = [("hello",), ("world",), ("how is life",)]

writer = DatasetWriter(DATA_PATH, {"text": JSONField()})
writer.from_indexed_dataset(data)

loader = Loader(DATA_PATH, batch_size=1)

for item in loader:
    print("raw out\t", item)
    print("decoded\n", JSONField.unpack(item[0])[0])