Changes in response to review. (1059672d) · Commits · 钟慕尧 / deepchem

deep_chem/models/deep3d.py

+4 −4

Original line number	Diff line number	Diff line
		@@ -16,6 +16,8 @@ from deep_chem.utils.evaluate import compute_r2_scores

		# TODO(rbharath): Factor this out into a separate function in utils. Duplicates
		# code in deep.py
		# TODO(rbharath): paths is to handle sharded input pickle files. Might be
		# better to use hdf5 datasets like in MSMBuilder
		def process_3D_convolutions(paths, task_transforms, seed=None, splittype="random"):
		"""Loads 3D Convolution datasets.

		@@ -50,7 +52,6 @@ def fit_3D_convolution(paths, task_types, task_transforms, axis_length=32, **tra
		modeltype="keras", mode="tensor")
		local_task_types = task_types.copy()
		r2s = compute_r2_scores(results, local_task_types)
		if r2s:
		print "Mean R^2: %f" % np.mean(np.array(r2s.values()))

		def train_3D_convolution(X, y, axis_length=32, batch_size=50, nb_epoch=1):
		@@ -82,8 +83,7 @@ def train_3D_convolution(X, y, axis_length=32, batch_size=50, nb_epoch=1):
		nb_conv = [7, 5, 3]

		model = Sequential()
		# TODO(rbharath): Avoid hard coding the number of staks here
		model.add(Convolution3D(nb_filter=nb_filters[0], stack_size=3,
		model.add(Convolution3D(nb_filter=nb_filters[0], stack_size=n_channels,
		nb_row=nb_conv[0], nb_col=nb_conv[0], nb_depth=nb_conv[0],
		border_mode='valid'))
		model.add(Activation('relu'))