Change preset optimize_for --> name

[npatki]

Problem Description

Currently, the new Preset configuration names are passed in using the optimize_for parameter. We should change this to name instead.

Expected behavior

In #716, update the param to name instead of optimize_for

>>> from sdv.lite import TabularPreset

# the PresetModel will not allow too many extra settings, making it simple to use
>>> model = TabularPreset(name='SPEED', metadata=my_metadata)
Info: This config optimizes the modeling speed above all else.

Your exact runtime is dependent on the data. Benchmarks:
100K rows and 100 columns may take around 1 minute.
1M rows and 250 columns may take around 30 minutes.

Also update the Error message when this param isn't passed in.

>>> model = TabularPreset()
Error: You must provide the name of a preset using the 'name' parameter. Use 
'TabularPreset.list_available_presets()' to browse through the options.

In #717, update the string to 'name' instead of 'optimize_for'

>>> from sdv.lite import TabularPreset
>>> TabularPreset.list_available_presets()
Available presets:
    "SPEED": Use this preset to minimize the time needed to create a synthetic data model

Supply the preset using the 'name' parameter.

Have any requests for custom presets? Contact the SDV team to learn more an SDV Premium license.

Additional context

<Please provide any additional context that may be relevant to the issue here. If none, please remove this section.>

[bhaveshneekhra]

Is this changed back to 'optimise_for' instead of 'name'. I could use 'name' and 'FAST_ML' few hours ago, but now it is asking for 'optimise_for' and 'SPEED'

Here is the output with sdv 0.14.1:

Available presets:
"SPEED": Use this preset to minimize the time needed to create a synthetic data model

Supply the preset using the 'optimise_for' parameter.

Have any requests for custom presets? Contact the SDV team to learn more an SDV Premium license.

[npatki]

Hi @bhaveshneekhra, this is particular issue was only present during the development phase. We never released any SDV version that asked for SPEED.

How are you installing SDV (cloning the repo, pip install, conda...)? Could you try a fresh install of SDV, preferably with pip? If the problem persists, we'd appreciate it if you could file a new issue with the trace and any steps we can take to reproduce.