Merge pull request #910 from miaecle/jenkins (1a764260) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorflow_models/lr.py

+1 −3

Original line number	Diff line number	Diff line
		@@ -243,8 +243,6 @@ class TensorflowLogisticRegression(TensorflowGraphModel):
		raise ValueError('Unrecognized rank combination for output: %s' %
		(batch_output.shape,))
		output.append(batch_output)

		outputs = np.array(
		from_one_hot(np.squeeze(np.concatenate(output)), axis=-1))
		outputs = np.array(from_one_hot(np.concatenate(output), axis=-1))

		return np.copy(outputs)

+8 −10

Original line number	Diff line number	Diff line
		@@ -160,15 +160,12 @@ class RobustMultitaskClassifier(TensorflowMultiTaskClassifier):
		task_layer_size = layer_sizes[-1]
		print("Adding output weights of shape %s" % str([task_layer_size, 1]))
		output.append(
		tf.squeeze(
		model_ops.logits(
		task_layer,
		num_classes=2,
		weight_init=tf.truncated_normal(
		shape=[task_layer_size, 2],
		stddev=weight_init_stddevs[-1]),
		bias_init=tf.constant(
		value=bias_init_consts[-1], shape=[2]))))
		shape=[task_layer_size, 2], stddev=weight_init_stddevs[-1]),
		bias_init=tf.constant(value=bias_init_consts[-1], shape=[2])))
		return (output, labels, weights)


		@@ -328,5 +325,6 @@ class RobustMultitaskRegressor(TensorflowMultiTaskRegressor):
		shape=[task_layer_size, 1],
		stddev=weight_init_stddevs[-1]),
		bias_init=tf.constant(
		value=bias_init_consts[-1], shape=[1]))))
		value=bias_init_consts[-1], shape=[1])),
		axis=1))
		return (output, labels, weights)

+16 −5

Original line number	Diff line number	Diff line
		@@ -7,12 +7,23 @@ BENCHMARK_TO_DESIRED_KEY_MAP = {
		"index": "Index splitting",
		"random": "Random splitting",
		"scaffold": "Scaffold splitting",
		"logreg": "logistic regression",
		"tf": "Multitask network",
		"tf_robust": "robust MT-NN",
		"logreg": "Logistic regression",
		"rf": "Random forest",
		"tf": "NN classification",
		"tf_robust": "Robust NN",
		"tf_regression": "NN regression",
		"graphconv": "graph convolution",
		"graphconvreg": "graphconv regression",
		"tf_regression_ft": "NN regression(CM)",
		"graphconv": "Graph convolution",
		"graphconvreg": "Graphconv regression",
		"irv": "IRV",
		"dag": "DAG",
		"dag_regression": "DAG regression",
		"dtnn": "DTNN",
		"mpnn": "MPNN",
		"weave": "Weave",
		"weave_regression": "Weave regression",
		"xgb": "XGBoost",
		"xgb_regression": "XGBoost regression"
		}
		DESIRED_RESULTS_CSV = "devtools/jenkins/desired_results.csv"
		TEST_RESULTS_CSV = "examples/results.csv"