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eval.py
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eval.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Trainer script. Example run command: bin/train.py save_to_folder configs/cnn.gin.
"""
import os
import gin
from gin.config import _CONFIG
import torch
import pickle
import logging
from functools import partial
logger = logging.getLogger(__name__)
from src import dataset
from src import callbacks as avail_callbacks
from src.model import MMTM_MVCNN
from src.training_loop import evalution_loop
from src.utils import gin_wrap
from train import blend_loss, acc
@gin.configurable
def eval_(save_path,
target_data_split,
pretrained_weights_path,
batch_size=128,
callbacks=[],
):
model = MMTM_MVCNN()
train, val, testing = dataset.get_mvdcndata(batch_size=batch_size)
if target_data_split == 'test':
target_data = testing
elif target_data_split == 'train':
target_data = train
elif target_data_split == 'val':
target_data = val
else:
raise NotImplementedError
# Create dynamically callbacks
callbacks_constructed = []
for name in callbacks:
if name in avail_callbacks.__dict__:
clbk = avail_callbacks.__dict__[name]()
callbacks_constructed.append(clbk)
evalution_loop(model=model,
loss_function=blend_loss,
metrics=[acc],
config=_CONFIG,
save_path=save_path,
test=target_data,
test_steps=len(target_data),
custom_callbacks=callbacks_constructed,
pretrained_weights_path=pretrained_weights_path)
if __name__ == "__main__":
gin_wrap(eval_)