Data Science

Describe the bug

The binary classifier error message in _get_response:

    classification_error = "{} should be a bin

Screenshot

Description

chart 3 dot menu is behind the chart title panel in chart maximize mode

Apache Arrow has a first-class tabular file format, Feather, that the Ray Datasets IO layer should support. Combined with Ray Datasets' existing .from_arrow() and .to_arrow() APIs, this would round out our "all-Arrow" experience, which should be as nice as possible given our "distributed Arrow dataset" positioning.

Implementation Note

We currently print a warning as shown below when a user sets both a widget default value in the function defining the widget as well as a widget value via the widget's key in st.session_state

While we certainly want to do this by default since doing both is not recommended, we should provide a

The docs for IPython.core.interactiveshell.InteractiveShell.set_custom_exc have horribly mangled a warning message into a list of arguments. I can't work out at a glance why this is happening; it might be a sphinx.ext.napoleon bug, or a sphi

In recent versions (can't say from exactly when), there seems to be an off-by-one error in dcc.DatePickerRange. I set max_date_allowed = datetime.today().date(), but in the calendar, yesterday is the maximum date allowed. I see it in my apps, and it is also present in the first example on the DatePickerRange documentation page.

E

Discussed in PyTorchLightning/pytorch-lightning#8630

I have a single GPU, but I would like to spawn multiple replicas on that single GPU and train a model with DDP. Of course, each replica would have to use a smaller batch size in order to fit in memory. (For my use case, I am not interested in having a single replica with a large batch size). I tried to pas

Bug summary

The new matplotlib.colors.make_norm_from_scale helper dynamically generates a norm class from a scale class. Currently, in the codebase, it is only used as a decorator to create "toplevel" classes (e.g., it is used to generate LogNorm from LogScale, etc.), but it can also be used within other functions to dynamically generate a norm class based on a user-given arbitrary scale (

In gensim/models/fasttext.py:

    model = FastText(
        vector_size=m.dim,
        vector_size=m.dim,
        window=m.ws,
        window=m.ws,
        epochs=m.epoch,
        epochs=m.epoch,
        negative=m.neg,
        negative=m.neg,
        # FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
        # or model=3 supervi

Is your feature request related to a problem? Please describe.
I want to evaluate multiple datasets (same formatting, they can share the same dataset reader). The "evaluate" command takes much longer to load the model than to evaluate.

Describe the solution you'd like
support passing multiple input files and output files to the "evaluate" command

**Describe alternatives you've cons