mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-27 23:47:46 +00:00
Linlang
d3c59b2f33
* use np.ndarray in costeer model evaluators * remove package * fix test error --------- Co-authored-by: Xu Yang <peteryang@vip.qq.com>
21 lines
761 B
Plaintext
21 lines
761 B
Plaintext
import os
|
|
import pickle
|
|
|
|
import numpy as np
|
|
import pandas as pd
|
|
import torch
|
|
from model import fit, predict
|
|
|
|
train_X = pd.DataFrame(np.random.randn(8, 30), columns=[f"{i}" for i in range(30)])
|
|
train_y = pd.Series(np.random.randint(0, 2, 8))
|
|
valid_X = pd.DataFrame(np.random.randn(8, 30), columns=[f"{i}" for i in range(30)])
|
|
valid_y = pd.Series(np.random.randint(0, 2, 8))
|
|
|
|
model = fit(train_X, train_y, valid_X, valid_y)
|
|
execution_model_output = predict(model, valid_X).cpu().detach().numpy()
|
|
|
|
execution_feedback_str = f"Execution successful, output numpy ndarray shape: {execution_model_output.shape}"
|
|
|
|
pickle.dump(execution_model_output, open("execution_model_output.pkl", "wb"))
|
|
pickle.dump(execution_feedback_str, open("execution_feedback_str.pkl", "wb"))
|