import os
import tempfile
import shutil
import numpy as np
import deepchem as dc
from KINASE_datasets import load_kinase
# Set numpy seed
np.random.seed(123)
###Load data###
shard_size = 2000
num_trials = 5
print("About to load KINASE data.")
KINASE_tasks, datasets, transformers = load_kinase(shard_size=shard_size)
train_dataset, valid_dataset, test_dataset = datasets
print("Number of compounds in train set")
print(len(train_dataset))
print("Number of compounds in validation set")
print(len(valid_dataset))
print("Number of compounds in test set")
print(len(test_dataset))
all_results = []
for trial in range(num_trials):
###Create model###
n_layers = 3
nb_epoch = 50
model = dc.models.TensorflowMultitaskRegressor(
from __future__ import division
from __future__ import unicode_literals
import os
import tempfile
import shutil
import numpy as np
import deepchem as dc
from KINASE_datasets import load_kinase
###Load data###
shard_size = 2000
#num_trials = 5
num_trials = 1
print("About to load KINASE data.")
KINASE_tasks, datasets, transformers = load_kinase(shard_size=shard_size)
train_dataset, valid_dataset, test_dataset = datasets
print("Number of compounds in train set")
print(len(train_dataset))
print("Number of compounds in validation set")
print(len(valid_dataset))
print("Number of compounds in test set")
print(len(test_dataset))
all_results = []
for trial in range(num_trials):
###Create model###
n_layers = 3
nb_epoch = 50
model = dc.models.ProgressiveMultitaskRegressor(