augmentedManifestFile + PipeModeDataset example

It would really help to have a full end to end example of, say, image classification with augmentedManifestFile + PipeModeDataset

as I keep getting errors of formats like
`tensorflow/core/framework/op_kernel.cc:1622] OP_REQUIRES failed at example_parsing_ops.cc:240 : Invalid argument: Could not parse example input, value: '����`

I build a jsonl augumentedManifest with
```
{'image-ref': s3://path/to/image, 'label': 3}
{'image-ref': s3://path/to/image, 'label': 1}
{'image-ref': s3://path/to/image, 'label': 2}
```
then preparing training channel as
```
train_data = sagemaker.session.s3_input(augmented_manifest_file_on_s3,
distribution = 'FullyReplicated',
content_type = 'image/jpeg',
s3_data_type = 'AugmentedManifestFile',
attribute_names = ['image-ref', 'label'],
input_mode = 'Pipe',
record_wrapping = 'RecordIO')

```
and launching the `.fit` as
```
data_channels = {'train': train_data}

# Train a model.
tf_estimator.fit(inputs=data_channels, logs=True)
```

in my entry script, I have
```
dataset = PipeModeDataset(channel = channel)
dataset = dataset.prefetch(tf.data.experimental.AUTOTUNE)
dataset = dataset.batch(2)
dataset = dataset.map(combine)
dataset = dataset.map(example_parser, num_parallel_calls=batch_size)
dataset = dataset.repeat(epochs)
dataset = dataset.batch(batch_size, drop_remainder=True)
image_batch, label_batch = next(iter(dataset))

```

and as a modified example parser, I have

`def example_parser(exemple1, exemple2):

feat1 = tf.io.parse_single_example(
exemple1,
features={
'image-ref' : tf.io.FixedLenFeature([], tf.string),
})

feat2 = tf.io.parse_single_example(
exemple2,
features={
'label' : tf.io.FixedLenFeature([], tf.int64),
})

image = feat1['image-ref']
image = tf.image.decode_jpeg(image, channels=3)
image = tf.image.convert_image_dtype(image, tf.float32)
label = tf.cast(feat2['label'], tf.int32)
return image, label
`

What am I doing wrong ?
The documentation [here](https://sagemaker.readthedocs.io/en/stable/using_tf.html#training-with-pipe-mode-using-pipemodedataset) is not clear about using augmented manifest files

Start with the linked training-with-PipeModeDataset documentation and the issue's augmentedManifestFile, PipeModeDataset, and example_parser entry points. Trace the supplied end-to-end training flow and document a working image-classification example, including the manifest format, channel configuration, dataset parsing, and what successful completion looks like.

Written by the indexing model from the issue text.