ImageEmbedder Docs: Fix print and remove embedding_dim usage

[tszumowski]

What does this PR do?

• Fix the prints in the examples so that they don't error, and so they print the desired format
• Remove embedding_dim usage in examples since it shouldn't be used unless fine tuning is included

Fixes #656

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• Did you make sure to update the documentation with your changes?
• Did you write any new necessary tests? [not needed for typos/docs]
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[tszumowski]

Test: Validate image_embedder.py Example

$ python3 flash_examples/image_embedder.py 

/home/szumowskit1/.venv/flash001/lib/python3.7/site-packages/urllib3/connectionpool.py:1020: InsecureRequestWarning: Unverified HTTPS request is being made to host 'pl-flash-data.s3.amazonaws.com'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings
  InsecureRequestWarning,
data/hymenoptera_data.zip: 67335KB [00:00, 69727.30KB/s]                                                                          
/home/szumowskit1/workspace/lightning-flash/flash/core/model.py:397: LightningDeprecationWarning: The `LightningModule.datamodule` property is deprecated in v1.3 and will be removed in v1.5. Access the datamodule through using `self.trainer.datamodule` instead.
  if self.datamodule is not None and getattr(self.datamodule, "data_pipeline", None) is not None:
/home/szumowskit1/.venv/flash001/lib/python3.7/site-packages/torch/nn/functional.py:3613: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
  "See the documentation of nn.Upsample for details.".format(mode)
/home/szumowskit1/.venv/flash001/lib/python3.7/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at  /pytorch/c10/core/TensorImpl.h:1156.)
  return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)
tensor([0.0847, 0.1147, 1.3101,  ..., 1.0288, 0.6192, 0.5854])
(flash001) szumowskit1@pytorch-1-9-20210810-141644:~/workspace/lightning-flash$  cd /home/szumowskit1/workspace/lightning-flash ; /usr/bin/env /home/szumowskit1/.venv/flash001/bin/python /home/szumowskit1/.vscode-server/extensions/ms-python.python-2021.8.1105858891/pythonFiles/lib/python/debugpy/launcher 43433 -- /home/szumowskit1/workspace/lightning-flash/flash_examples/image_embedder.py 
/home/szumowskit1/.venv/flash001/lib/python3.7/site-packages/urllib3/connectionpool.py:1020: InsecureRequestWarning: Unverified HTTPS request is being made to host 'pl-flash-data.s3.amazonaws.com'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings
  InsecureRequestWarning,
/home/szumowskit1/workspace/lightning-flash/flash/core/model.py:397: LightningDeprecationWarning: The `LightningModule.datamodule` property is deprecated in v1.3 and will be removed in v1.5. Access the datamodule through using `self.trainer.datamodule` instead.
  if self.datamodule is not None and getattr(self.datamodule, "data_pipeline", None) is not None:
/home/szumowskit1/.venv/flash001/lib/python3.7/site-packages/torch/nn/functional.py:3613: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
  "See the documentation of nn.Upsample for details.".format(mode)
/home/szumowskit1/.venv/flash001/lib/python3.7/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at  /pytorch/c10/core/TensorImpl.h:1156.)
  return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)
[tensor([0.0847, 0.1147, 1.3101,  ..., 1.0288, 0.6192, 0.5854])]

The last line shows it still runs end to end.

[codecov]

Codecov Report

Merging #665 (34ab4a9) into master (c40f384) will increase coverage by 1.37%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master     #665      +/-   ##
==========================================
+ Coverage   87.98%   89.36%   +1.37%     
==========================================
  Files         185      185              
  Lines        9663     9663              
==========================================
+ Hits         8502     8635     +133     
+ Misses       1161     1028     -133     

Flag	Coverage Δ
unittests	89.36% <ø> (+1.37%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
flash/text/seq2seq/translation/model.py	76.19% <0.00%> (+4.76%)	⬆️
flash/text/seq2seq/summarization/model.py	80.00% <0.00%> (+5.00%)	⬆️
flash/text/seq2seq/core/model.py	75.36% <0.00%> (+8.69%)	⬆️
flash/text/seq2seq/core/data.py	89.87% <0.00%> (+21.51%)	⬆️
flash/text/classification/model.py	93.18% <0.00%> (+22.72%)	⬆️
flash/text/seq2seq/core/metrics.py	97.22% <0.00%> (+23.14%)	⬆️
flash/text/classification/data.py	91.01% <0.00%> (+28.08%)	⬆️
flash/text/classification/cli.py	100.00% <0.00%> (+42.85%)	⬆️

---

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[tszumowski]

Test: Validate README Example

---

Executed README code:

from flash.core.data.utils import download_data
from flash.image import ImageEmbedder

# 1. Download the data
download_data("https://pl-flash-data.s3.amazonaws.com/hymenoptera_data.zip", "data/")

# 2. Create an ImageEmbedder with resnet50 trained on imagenet.
embedder = ImageEmbedder(backbone="resnet50")

# 3. Generate an embedding from an image path.
embeddings = embedder.predict("data/hymenoptera_data/predict/153783656_85f9c3ac70.jpg")

# 4. Print embeddings shape
print(embeddings[0].shape)

Output:

/home/szumowskit1/.venv/flash001/lib/python3.7/site-packages/urllib3/connectionpool.py:1020: InsecureRequestWarning: Unverified HTTPS request is being made to host 'pl-flash-data.s3.amazonaws.com'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings
  InsecureRequestWarning,
/home/szumowskit1/workspace/lightning-flash/flash/core/model.py:397: LightningDeprecationWarning: The `LightningModule.datamodule` property is deprecated in v1.3 and will be removed in v1.5. Access the datamodule through using `self.trainer.datamodule` instead.
  if self.datamodule is not None and getattr(self.datamodule, "data_pipeline", None) is not None:
/home/szumowskit1/.venv/flash001/lib/python3.7/site-packages/torch/nn/functional.py:3613: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
  "See the documentation of nn.Upsample for details.".format(mode)
/home/szumowskit1/.venv/flash001/lib/python3.7/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at  /pytorch/c10/core/TensorImpl.h:1156.)
  return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)
torch.Size([2048])

Last line shows it working.
Prior to this, running without the change in this PR gives:

Traceback (most recent call last):
  File "/home/szumowskit1/workspace/lightning-flash/tmp.py", line 14, in <module>
    print(embeddings.shape)
AttributeError: 'list' object has no attribute 'shape'

[ethanwharris]

Awesome! LGTM 😃