Loading deepchem/models/tensorflow_models/IRV.py +46 −22 Original line number Diff line number Diff line Loading @@ -11,13 +11,23 @@ from deepchem.models.tensorflow_models import TensorflowGraph from deepchem.models.tensorflow_models import TensorflowGraphModel from deepchem.models.tensorflow_models.lr import TensorflowLogisticRegression class TensorflowMultiTaskIRVClassifier(TensorflowLogisticRegression): def __init__(self, n_tasks, K=10, logdir=None, n_classes=2, penalty=0.0, penalty_type="l2", learning_rate=0.001, momentum=.8, optimizer="adam", batch_size=50, verbose=True, seed=None, def __init__(self, n_tasks, K=10, logdir=None, n_classes=2, penalty=0.0, penalty_type="l2", learning_rate=0.001, momentum=.8, optimizer="adam", batch_size=50, verbose=True, seed=None, **kwargs): """Initialize TensorflowMultiTaskIRVClassifier Parameters Loading Loading @@ -53,12 +63,25 @@ class TensorflowMultiTaskIRVClassifier(TensorflowLogisticRegression): self.K = K self.n_features = 2 * self.K * self.n_tasks print("n_features after fit_transform: %d" % int(self.n_features)) TensorflowGraphModel.__init__(self, n_tasks, self.n_features, logdir=logdir, layer_sizes=None, weight_init_stddevs=None, bias_init_consts=None, penalty=penalty, penalty_type=penalty_type, dropouts=None, n_classes=n_classes, learning_rate=learning_rate, momentum=momentum, optimizer=optimizer, batch_size=batch_size, pad_batches=False, verbose=verbose, seed=seed, TensorflowGraphModel.__init__( self, n_tasks, self.n_features, logdir=logdir, layer_sizes=None, weight_init_stddevs=None, bias_init_consts=None, penalty=penalty, penalty_type=penalty_type, dropouts=None, n_classes=n_classes, learning_rate=learning_rate, momentum=momentum, optimizer=optimizer, batch_size=batch_size, pad_batches=False, verbose=verbose, seed=seed, **kwargs) def build(self, graph, name_scopes, training): Loading @@ -66,8 +89,8 @@ class TensorflowMultiTaskIRVClassifier(TensorflowLogisticRegression): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2750043/ """ placeholder_scope = TensorflowGraph.get_placeholder_scope( graph, name_scopes) placeholder_scope = TensorflowGraph.get_placeholder_scope(graph, name_scopes) K = self.K with graph.as_default(): output = [] Loading @@ -81,10 +104,11 @@ class TensorflowMultiTaskIRVClassifier(TensorflowLogisticRegression): b2 = tf.Variable(tf.constant([0.01]), name="b2", dtype=tf.float32) for count in range(self.n_tasks): similarity = self.features[:, 2 * K * count:(2 * K * count + K)] ys = tf.to_int32(self.features[:, (2*K*count+K):2*K*(count+1)]) R = b+W[0]*similarity+W[1]*tf.constant(np.arange(K)+1, dtype=tf.float32) ys = tf.to_int32( self.features[:, (2 * K * count + K):2 * K * (count + 1)]) R = b + W[0] * similarity + W[1] * tf.constant( np.arange(K) + 1, dtype=tf.float32) R = tf.sigmoid(R) z = tf.reduce_sum(R * tf.gather(V, ys), axis=1) + b2 output.append(tf.reshape(z, shape=[-1, 1])) return output deepchem/trans/transformers.py +11 −13 Original line number Diff line number Diff line Loading @@ -606,13 +606,13 @@ class CoulombFitTransformer(): def untransform(self, z): raise NotImplementedError( <<<<<<< HEAD "Cannot untransform datasets with FitTransformer.") class IRVTransformer(): """Performs transform from ECFP to IRV features(K nearest neibours).""" def __init__(self, K, n_tasks, dataset, transform_y=False, transform_x=False): def __init__(self, K, n_tasks, dataset, transform_y=False, transform_x=False): """Initializes IRVTransformer. Parameters: ---------- Loading Loading @@ -647,7 +647,8 @@ class IRVTransformer(): def X_transform(self, X_target): X_target2 = [] similarity = np.matmul(X_target, np.transpose(self.X))/(1024-np.matmul(1-X_target, np.transpose(1-self.X))) similarity = np.matmul(X_target, np.transpose(self.X)) / ( 1024 - np.matmul(1 - X_target, np.transpose(1 - self.X))) for i in range(self.n_tasks): X_target2.append(self.realize(similarity, self.y[:, i], self.w[:, i])) return np.concatenate([z for z in np.array(X_target2)], axis=1) Loading @@ -659,6 +660,3 @@ class IRVTransformer(): def untransform(self, z): raise NotImplementedError( "Cannot untransform datasets with IRVTransformer.") ======= "Cannot untransform datasets with FitTransformer.") >>>>>>> remotes/origin/master examples/tox21/tox21_IRV.py +9 −6 Original line number Diff line number Diff line Loading @@ -38,10 +38,13 @@ for transformer in transformers: test_dataset = transformer.transform(test_dataset) print("end") model = dc.models.TensorflowMultiTaskIRVClassifier( len(tox21_tasks), K=K, learning_rate=0.001, penalty = 0.05, batch_size=32, fit_transformers=[]) len(tox21_tasks), K=K, learning_rate=0.001, penalty=0.05, batch_size=32, fit_transformers=[]) # Fit trained model model.fit(train_dataset, nb_epoch=10) Loading Loading
deepchem/models/tensorflow_models/IRV.py +46 −22 Original line number Diff line number Diff line Loading @@ -11,13 +11,23 @@ from deepchem.models.tensorflow_models import TensorflowGraph from deepchem.models.tensorflow_models import TensorflowGraphModel from deepchem.models.tensorflow_models.lr import TensorflowLogisticRegression class TensorflowMultiTaskIRVClassifier(TensorflowLogisticRegression): def __init__(self, n_tasks, K=10, logdir=None, n_classes=2, penalty=0.0, penalty_type="l2", learning_rate=0.001, momentum=.8, optimizer="adam", batch_size=50, verbose=True, seed=None, def __init__(self, n_tasks, K=10, logdir=None, n_classes=2, penalty=0.0, penalty_type="l2", learning_rate=0.001, momentum=.8, optimizer="adam", batch_size=50, verbose=True, seed=None, **kwargs): """Initialize TensorflowMultiTaskIRVClassifier Parameters Loading Loading @@ -53,12 +63,25 @@ class TensorflowMultiTaskIRVClassifier(TensorflowLogisticRegression): self.K = K self.n_features = 2 * self.K * self.n_tasks print("n_features after fit_transform: %d" % int(self.n_features)) TensorflowGraphModel.__init__(self, n_tasks, self.n_features, logdir=logdir, layer_sizes=None, weight_init_stddevs=None, bias_init_consts=None, penalty=penalty, penalty_type=penalty_type, dropouts=None, n_classes=n_classes, learning_rate=learning_rate, momentum=momentum, optimizer=optimizer, batch_size=batch_size, pad_batches=False, verbose=verbose, seed=seed, TensorflowGraphModel.__init__( self, n_tasks, self.n_features, logdir=logdir, layer_sizes=None, weight_init_stddevs=None, bias_init_consts=None, penalty=penalty, penalty_type=penalty_type, dropouts=None, n_classes=n_classes, learning_rate=learning_rate, momentum=momentum, optimizer=optimizer, batch_size=batch_size, pad_batches=False, verbose=verbose, seed=seed, **kwargs) def build(self, graph, name_scopes, training): Loading @@ -66,8 +89,8 @@ class TensorflowMultiTaskIRVClassifier(TensorflowLogisticRegression): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2750043/ """ placeholder_scope = TensorflowGraph.get_placeholder_scope( graph, name_scopes) placeholder_scope = TensorflowGraph.get_placeholder_scope(graph, name_scopes) K = self.K with graph.as_default(): output = [] Loading @@ -81,10 +104,11 @@ class TensorflowMultiTaskIRVClassifier(TensorflowLogisticRegression): b2 = tf.Variable(tf.constant([0.01]), name="b2", dtype=tf.float32) for count in range(self.n_tasks): similarity = self.features[:, 2 * K * count:(2 * K * count + K)] ys = tf.to_int32(self.features[:, (2*K*count+K):2*K*(count+1)]) R = b+W[0]*similarity+W[1]*tf.constant(np.arange(K)+1, dtype=tf.float32) ys = tf.to_int32( self.features[:, (2 * K * count + K):2 * K * (count + 1)]) R = b + W[0] * similarity + W[1] * tf.constant( np.arange(K) + 1, dtype=tf.float32) R = tf.sigmoid(R) z = tf.reduce_sum(R * tf.gather(V, ys), axis=1) + b2 output.append(tf.reshape(z, shape=[-1, 1])) return output
deepchem/trans/transformers.py +11 −13 Original line number Diff line number Diff line Loading @@ -606,13 +606,13 @@ class CoulombFitTransformer(): def untransform(self, z): raise NotImplementedError( <<<<<<< HEAD "Cannot untransform datasets with FitTransformer.") class IRVTransformer(): """Performs transform from ECFP to IRV features(K nearest neibours).""" def __init__(self, K, n_tasks, dataset, transform_y=False, transform_x=False): def __init__(self, K, n_tasks, dataset, transform_y=False, transform_x=False): """Initializes IRVTransformer. Parameters: ---------- Loading Loading @@ -647,7 +647,8 @@ class IRVTransformer(): def X_transform(self, X_target): X_target2 = [] similarity = np.matmul(X_target, np.transpose(self.X))/(1024-np.matmul(1-X_target, np.transpose(1-self.X))) similarity = np.matmul(X_target, np.transpose(self.X)) / ( 1024 - np.matmul(1 - X_target, np.transpose(1 - self.X))) for i in range(self.n_tasks): X_target2.append(self.realize(similarity, self.y[:, i], self.w[:, i])) return np.concatenate([z for z in np.array(X_target2)], axis=1) Loading @@ -659,6 +660,3 @@ class IRVTransformer(): def untransform(self, z): raise NotImplementedError( "Cannot untransform datasets with IRVTransformer.") ======= "Cannot untransform datasets with FitTransformer.") >>>>>>> remotes/origin/master
examples/tox21/tox21_IRV.py +9 −6 Original line number Diff line number Diff line Loading @@ -38,10 +38,13 @@ for transformer in transformers: test_dataset = transformer.transform(test_dataset) print("end") model = dc.models.TensorflowMultiTaskIRVClassifier( len(tox21_tasks), K=K, learning_rate=0.001, penalty = 0.05, batch_size=32, fit_transformers=[]) len(tox21_tasks), K=K, learning_rate=0.001, penalty=0.05, batch_size=32, fit_transformers=[]) # Fit trained model model.fit(train_dataset, nb_epoch=10) Loading
