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Description
Hello!
I found an AI-Specific Code smell in your project.
The smell is called: Columns and DataType Not Explicitly Set
You can find more information about it in this paper: https://dl.acm.org/doi/abs/10.1145/3522664.3528620.
According to the paper, the smell is described as follows:
Problem | If the columns are not selected explicitly, it is not easy for developers to know what to expect in the downstream data schema. If the datatype is not set explicitly, it may silently continue the next step even though the input is unexpected, which may cause errors later. The same applies to other data importing scenarios. |
---|---|
Solution | It is recommended to set the columns and DataType explicitly in data processing. |
Impact | Readability |
Example:
### Pandas Column Selection
import pandas as pd
df = pd.read_csv('data.csv')
+ df = df[['col1', 'col2', 'col3']]
### Pandas Set DataType
import pandas as pd
- df = pd.read_csv('data.csv')
+ df = pd.read_csv('data.csv', dtype={'col1': 'str', 'col2': 'int', 'col3': 'float'})
You can find the code related to this smell in this link:
tcav/tcav/tcav_examples/image_models/imagenet/imagenet_and_broden_fetcher.py
Lines 59 to 79 in ef3bb59
Reads a csv file containing matches between imagenet synids and the url in | |
which we can fetch them. Appending the synid to kImagenetBaseUrl will fetch all | |
the URLs of images for a given imagenet label | |
Args: path_to_imagenet_classes: String. Points to a csv file matching | |
imagenet labels with synids. | |
Returns: a pandas dataframe with keys {url: _ , class_name: _ , synid: _} | |
""" | |
def make_imagenet_dataframe(path_to_imagenet_classes): | |
urls_dataframe = pd.read_csv(path_to_imagenet_classes) | |
urls_dataframe["url"] = kImagenetBaseUrl + urls_dataframe["synid"] | |
return urls_dataframe | |
""" Downloads an image. | |
Downloads and image from a image url provided and saves it under path. | |
Filters away images that are corrupted or smaller than 10KB | |
Args: | |
path: Path to the folder where we're saving this image. |
I also found instances of this smell in other files, such as:
File: https://github.com/tensorflow/tcav/blob/master/tcav/tcav_examples/discrete/make_kdd99_concepts.py#L54-L64 Line: 59
.
I hope this information is helpful!
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