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72 lines
2.6 KiB
Python
72 lines
2.6 KiB
Python
def test_classification_head():
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from flaml import AutoML
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import pandas as pd
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import requests
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train_data = {
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"text": [
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"i didnt feel humiliated",
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"i can go from feeling so hopeless to so damned hopeful just from being around someone who cares and is awake",
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"im grabbing a minute to post i feel greedy wrong",
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"i am ever feeling nostalgic about the fireplace i will know that it is still on the property",
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"i am feeling grouchy",
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"ive been feeling a little burdened lately wasnt sure why that was",
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"ive been taking or milligrams or times recommended amount and ive fallen asleep a lot faster but i also feel like so funny",
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"i feel as confused about life as a teenager or as jaded as a year old man",
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"i have been with petronas for years i feel that petronas has performed well and made a huge profit",
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"i feel romantic too",
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"i feel like i have to make the suffering i m seeing mean something",
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"i do feel that running is a divine experience and that i can expect to have some type of spiritual encounter",
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],
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"label": [0, 0, 3, 2, 3, 0, 5, 4, 1, 2, 0, 1],
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}
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train_dataset = pd.DataFrame(train_data)
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dev_data = {
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"text": [
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"i think it s the easiest time of year to feel dissatisfied",
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"i feel low energy i m just thirsty",
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"i have immense sympathy with the general point but as a possible proto writer trying to find time to write in the corners of life and with no sign of an agent let alone a publishing contract this feels a little precious",
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"i do not feel reassured anxiety is on each side",
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],
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"label": [3, 0, 1, 1],
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}
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dev_dataset = pd.DataFrame(dev_data)
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custom_sent_keys = ["text"]
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label_key = "label"
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X_train = train_dataset[custom_sent_keys]
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y_train = train_dataset[label_key]
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X_val = dev_dataset[custom_sent_keys]
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y_val = dev_dataset[label_key]
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automl = AutoML()
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automl_settings = {
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"gpu_per_trial": 0,
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"max_iter": 3,
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"time_budget": 5,
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"task": "seq-classification",
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"metric": "accuracy",
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}
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automl_settings["custom_hpo_args"] = {
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"model_path": "google/electra-small-discriminator",
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"output_dir": "test/data/output/",
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"ckpt_per_epoch": 1,
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"fp16": False,
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}
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try:
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automl.fit(
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X_train=X_train,
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y_train=y_train,
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X_val=X_val,
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y_val=y_val,
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**automl_settings
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)
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except requests.exceptions.HTTPError:
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return
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