Leftover bugfixes (6844d31c) · Commits · 钟慕尧 / deepchem

deepchem/hyper/tests/test_hyperparam_opt.py

+2 −3

Original line number	Diff line number	Diff line
		@@ -165,9 +165,8 @@ class TestHyperparamOptAPI(unittest.TestCase):
		params_dict = {"layer_sizes": [(10,), (100,)]}

		def model_builder(model_params, model_dir):
		tensorflow_model = dc.models.TensorflowMultiTaskClassifier(
		return dc.models.TensorflowMultiTaskClassifier(
		len(tasks), n_features, model_dir, **model_params)
		return dc.models.TensorflowModel(tensorflow_model)
		optimizer = dc.hyper.HyperparamOpt(model_builder)
		best_model, best_hyperparams, all_results = optimizer.hyperparam_search(
		params_dict, train_dataset, valid_dataset, transformers, metric,

deepchem/models/tensorflow_models/init.py

+3 −9

Original line number	Diff line number	Diff line
		@@ -160,8 +160,6 @@ class TensorflowGraphModel(Model):
		self.train_graph = self.construct_graph(training=True)
		self.eval_graph = self.construct_graph(training=False)

		################################################################ DEBUG

		def save(self):
		"""
		No-op since tf models save themselves during fit()
		@@ -172,12 +170,10 @@ class TensorflowGraphModel(Model):
		"""
		Loads model from disk. Thin wrapper around restore() for consistency.
		"""
		self.model_instance.restore()
		self.restore()

		def get_num_tasks(self):
		return self.n_tasks
		################################################################ DEBUG


		def construct_graph(self, training):
		"""Returns a TensorflowGraph object."""
		@@ -281,8 +277,8 @@ class TensorflowGraphModel(Model):
		for ind, (X_b, y_b, w_b, ids_b) in enumerate(
		############################################################ DEBUG
		## hardcode pad_batches=True to work around limitations in Tensorflow
		#dataset.iterbatches(batch_size, pad_batches=True)):
		dataset.iterbatches(batch_size, pad_batches=False)):
		dataset.iterbatches(batch_size, pad_batches=True)):
		#dataset.iterbatches(batch_size, pad_batches=False)):
		#dataset.iterbatches(batch_size, pad_batches=pad_batches)):
		############################################################ DEBUG
		if ind % log_every_N_batches == 0:
		@@ -684,8 +680,6 @@ class TensorflowRegressor(TensorflowGraphModel):
		outputs = []
		with self._get_shared_session(train=False).as_default():
		n_samples = len(X)
		# TODO(rbharath): Should this be padding there? Shouldn't padding be
		# turned on in predict?
		feed_dict = self.construct_feed_dict(X)
		data = self._get_shared_session(train=False).run(
		self.eval_graph.output, feed_dict=feed_dict)

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