Ate pretrain 0506

[vincewu51]

Proposed changes

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Changes made

• add pretrain flag to each meta-learner's estimate_ate function, so when the model is already trained, the programm will skip the training.
• add the corresponding test to make sure the new method gives the same result
• add a simple example in https://github.com/uber/causalml/blob/master/examples/meta_learners_with_synthetic_data.ipynb

Links to related issues/PRs
#395

Tests
test/test_meta_learner.py

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• [X ] New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
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[jpansnap]

QQ: for S-learner if we already have the model, we could has have y=None here right? As what you did for R-leaner.

[vincewu51]

Yes you are right, but since self.predict here also accepts y, treatment as parameters, I included them here.

[vincewu51]

The checks are throwing error for file 'causalml/inference/tree/causaltree.pyx', but this diff didn't change anything for this file.

@jeongyoonlee Hi Jeong, do you have any past experience on this. The error is on cython.
causalml/inference/tree/causaltree.pyx:136:37: Cannot assign type 'double[::1]' to 'double *'

[vincewu51]

The checks are throwing error for file 'causalml/inference/tree/causaltree.pyx', but this diff didn't change anything for this file.

@jeongyoonlee Hi Jeong, do you have any past experience on this. The error is on cython. causalml/inference/tree/causaltree.pyx:136:37: Cannot assign type 'double[::1]' to 'double *'

The problem is solved by adding scikit-learn<=1.0.2 in requirement.txt. scikit learn released a new version 1.1.0 recently, it is causing the issue mentioned above. I'll create a separate issue on this.

Link to issue

[paullo0106]

LGTM, thanks!