update (c8fb17b8) · Commits · 钟慕尧 / deepchem

deepchem/hyper/gaussian_process.py

+15 −1

Original line number	Diff line number	Diff line
		@@ -7,6 +7,7 @@ from __future__ import unicode_literals

		import numpy as np
		import tempfile
		import os
		from deepchem.hyper.grid_search import HyperparamOpt
		from deepchem.utils.evaluate import Evaluator
		from deepchem.molnet.run_benchmark_models import benchmark_classification, benchmark_regression
		@@ -35,7 +36,8 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		'colsample_bylevel', 'colsample_bytree', 'reg_alpha',
		'reg_lambda', 'scale_pos_weight', 'base_score'
		],
		logdir=None):
		logdir=None,
		log_file='GPhypersearch.log')
		"""Perform hyperparams search using a gaussian process assumption

		params_dict include single-valued parameters being optimized,
		@@ -133,6 +135,8 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		param_name = ['l' + format(i, '02d') for i in range(20)]
		param = dict(zip(param_name[:n_param], param_range))

		data_dir = os.environ['DEEPCHEM_DATA_DIR']
		log_file = os.path.join(data_dir, log_file)
		def f(l00=0,
		l01=0,
		l02=0,
		@@ -185,6 +189,8 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):

		print(hyper_parameters)
		# Run benchmark
		with open(log_file, 'a') as f:
		f.write(hyper_parameters)
		if isinstance(self.model_class, str) or isinstance(
		self.model_class, unicode):
		try:
		@@ -216,6 +222,9 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		evaluator = Evaluator(model, valid_dataset, output_transformers)
		multitask_scores = evaluator.compute_model_performance([metric])
		score = multitask_scores[metric.name]

		with open(log_file, 'a') as f:
		f.write(score)
		if direction:
		return score
		else:
		@@ -248,6 +257,9 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		hyper_parameters[hp[0]] = map(int, hyper_parameters[hp[0]])
		i = i + hp[1]


		with open(log_file, 'a') as f:
		f.write(params_dict)
		if isinstance(self.model_class, str) or isinstance(
		self.model_class, unicode):
		try:
		@@ -271,6 +283,8 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		self.model_class,
		hyper_parameters=params_dict)
		score = valid_scores[self.model_class][metric[0].name]
		with open(log_file, 'a') as f:
		f.write(score)
		if not direction:
		score = -score
		if score > valid_performance_opt:

deepchem/molnet/preset_hyper_parameters.py

+2 −2

Original line number	Diff line number	Diff line
		@@ -153,8 +153,8 @@ hps['weave_regression'] = {
		'seed': 123
		}
		hps['ani'] = {
		'batch_size': 128,
		'nb_epoch': 300,
		'batch_size': 32,
		'nb_epoch': 50,
		'learning_rate': 0.001,
		'layer_structures': [128, 128, 64],
		'seed': 123

deepchem/trans/transformers.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -976,7 +976,7 @@ class ANITransformer(Transformer):
		self.transform_w = transform_w
		self.compute_graph = self.build()
		self.sess = tf.Session(graph=self.compute_graph)
		self.transform_batch_size = 128
		self.transform_batch_size = 32
		assert self.transform_X
		assert not self.transform_y
		assert not self.transform_w

examples/qm8rf_regression.pkl

0 → 100644

+5 −0

Original line number	Diff line number	Diff line
		(dp0
		S'n_estimators'
		p1
		I895
		s.
		No newline at end of file

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