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Deep Learning
breadbread1984
发布于 2024-02-02
推荐镜像 :Basic Image:ubuntu:22.04-py3.10-cuda12.1
推荐机型 :c2_m4_cpu
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事数据集(v3)
[1]
!pip install rdkit==2023.9.3 mordred==1.2.0 networkx==2.8.4 numpy==1.23.5 nose-py3 pandas pyyaml tensorflow wget
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
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Building wheels for collected packages: mordred, wget
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Successfully built mordred wget
Installing collected packages: wget, snowballstemmer, libclang, flatbuffers, 2to3, wrapt, werkzeug, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, sphinxcontrib-serializinghtml, sphinxcontrib-qthelp, sphinxcontrib-jsmath, sphinxcontrib-htmlhelp, sphinxcontrib-devhelp, sphinxcontrib-applehelp, pyasn1, protobuf, Pillow, oauthlib, numpy, networkx, markdown, keras, imagesize, grpcio, google-pasta, gast, docutils, coverage, cachetools, astunparse, alabaster, absl-py, sphinx, rsa, requests-oauthlib, rdkit, pyasn1-modules, opt-einsum, mordred, ml-dtypes, nose-py3, google-auth, google-auth-oauthlib, tensorboard, tensorflow
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WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
代码
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[2]
from os import environ
environ['CUDA_VISIBLE_DEVICES']='-1'
import tensorflow as tf

class GraphConvolution(tf.keras.layers.Layer):
def __init__(self, **kwargs):
super(GraphConvolution, self).__init__(**kwargs)
def build(self, input_shape):
self.bias = self.add_weight(name = 'bias', shape = (1,1,input_shape[1][-1]), initializer = tf.keras.initializers.GlorotUniform(), trainable = True)
def call(self, inputs):
# adjacent.shape = (batch, atom_num, atom_num)
# annotations.shape = (batch, atom_num, in_channel)
adjacent, annotations = inputs
results = list()
# NOTE: sparse_dense_matmul doesn't support matrix with batch dimension
for i in range(tf.shape(adjacent)[0]):
adj = tf.sparse.slice(adjacent, [i,0,0], [1,tf.shape(adjacent)[1],tf.shape(adjacent)[2]])
adj = tf.sparse.reshape(adj, [tf.shape(adjacent)[1], tf.shape(adjacent)[2]])
results.append(tf.sparse.sparse_dense_matmul(adj, annotations[i])) # results.shape = (batch, atom_num, in_channel)
results = tf.stack(results, axis = 0)
results = results + self.bias
return results

class GatedGraphConvolution(tf.keras.Model):
def __init__(self, channels, **kwargs):
super(GatedGraphConvolution, self).__init__(**kwargs)
self.gc = GraphConvolution()
self.gru = tf.keras.layers.GRU(channels)
self.channels = channels
def call(self, adjacent, annotations):
results = self.gc([adjacent, annotations]) # results.shape = (batch, atom_num, channels)
shape = tf.shape(results)
hidden_states = tf.reshape(annotations, (-1, self.channels)) # hidden_states.shape = (batch * atom_num, channels)
visible_states = tf.reshape(results, (-1, 1, self.channels)) # visible_states.shape = (batch * atom_num, 1, channels)
results = self.gru(visible_states, initial_state = hidden_states) # results.shape = (batch * atom_num, channels)
results = tf.reshape(results, shape) # results.shape = (batch, atom_num, channels)
return results

class FeatureExtractor(tf.keras.Model):
def __init__(self, channels = 32, num_layers = 4, **kwargs):
super(FeatureExtractor, self).__init__(**kwargs)
self.embed = tf.keras.layers.Embedding(118, channels)
self.ggnns = [GatedGraphConvolution(channels) for i in range(num_layers)]
self.pool = tf.keras.layers.Lambda(lambda x: tf.math.reduce_mean(x, axis = 1))
def call(self, adjacent, annotations):
results = self.embed(annotations) # results.shape = (batch, atom_num, 32)
for ggnn in self.ggnns:
results = ggnn(adjacent, results)
# graph pooling
results = self.pool(results) # results.shape = (batch, 32)
return results

class Predictor(tf.keras.Model):
def __init__(self, channels = 32, num_layers = 4, **kwargs):
super(Predictor, self).__init__(**kwargs)
self.extractor = FeatureExtractor(channels, num_layers, **kwargs)
self.dense = tf.keras.layers.Dense(1, activation = tf.keras.activations.sigmoid)
def call(self, adjacent, annotations):
results = self.extractor(adjacent, annotations)
results = self.dense(results)
return results
2024-02-02 12:08:16.584870: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-02-02 12:08:16.584943: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-02-02 12:08:16.586279: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-02-02 12:08:16.595134: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-02-02 12:08:17.648562: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
代码
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[6]
from wget import download
from os import system
from os.path import exists,join

if not exists('ckpt.tar.gz'): download('https://gitee.com/breadbread1984/molecule_attributes_prediction/raw/master/ckpt.tar.gz')
system('tar xzvf ckpt.tar.gz')
predictor = Predictor(channels = 256, num_layers = 4)
optimizer = tf.keras.optimizers.Adam(1e-2)
checkpoint = tf.train.Checkpoint(model = predictor, optimizer = optimizer)
checkpoint.restore(tf.train.latest_checkpoint('ckpt'))
ckpt/
ckpt/ckpt-21.index
ckpt/events.out.tfevents.1706780381.dgxa100svr02.540029.0.v2
ckpt/checkpoint
ckpt/ckpt-21.data-00000-of-00001

<tensorflow.python.checkpoint.checkpoint.CheckpointLoadStatus at 0x7f666022df30>
代码
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[7]
from rdkit import Chem

def smiles_to_graph(smiles: str):
molecule = Chem.MolFromSmiles(smiles)
atom_num = len(molecule.GetAtoms())
annotations = list()
indices = list()
values = list()
for atom in molecule.GetAtoms():
idx = atom.GetIdx()
annotations.append(atom.GetAtomicNum())
for neighbor_atom in atom.GetNeighbors():
neighbor_idx = neighbor_atom.GetIdx()
indices.append((idx, neighbor_idx))
# FIXME: bond type is not shown in adjacent matrix
#bond_type = molecule.GetBondBetweenAtoms(idx, neighbor_idx).GetBondType()
values.append(1)
adjacent = tf.cast(tf.sparse.reorder(tf.sparse.SparseTensor(indices = indices, values = values, dense_shape = (atom_num, atom_num))), dtype = tf.float32)
row_sum = tf.sparse.reduce_sum(adjacent, axis = -1, keepdims = True) # row_sum.shape = (atom_num, 1)
adjacent = adjacent / row_sum # normalization
annotations = tf.cast(tf.stack(annotations), dtype = tf.int32) # annotations.shape = (atom_num)
return adjacent, annotations

csv = open('/bohr/ai4scup-cns-5zkz/v3/mol_test.csv', 'r')
output = open('submission.csv', 'w')
output.write('SMILES,TARGET\n')
for line, row in enumerate(csv.readlines()):
if line == 0: continue
smiles, label = row.split(',')
adjacent, atoms = smiles_to_graph(smiles)
adjacent = tf.sparse.expand_dims(adjacent, axis = 0)
atoms = tf.expand_dims(atoms, axis = 0)
pred = predictor(adjacent, atoms)
print(smiles, pred[0])
output.write("%s,%d" % (smiles, 1 if pred[0] > 0.5 else 0) + '\n')
output.close()
csv.close()
CC(CCC(=O)O)C1CCC2C3C(CC(=O)C12C)C4(C)CCC(=O)CC4CC3=O tf.Tensor([0.15827034], shape=(1,), dtype=float32)
CC(=O)c1ccc2c(c1)Sc3ccccc3N2CCCN4CCN(CC4)CCO tf.Tensor([0.99103284], shape=(1,), dtype=float32)
CCCN(CCC)C(=O)C(CCC(=O)OCCCN1CCN(CCOC(=O)Cc2c(C)n(C(=O)c3ccc(Cl)cc3)c4ccc(OC)cc24)CC1)NC(=O)c5ccccc5 tf.Tensor([0.6153903], shape=(1,), dtype=float32)
CC(C)CCCC(C)CCCC(C)CCCC1(C)CCc2c(C)c(O)c(C)c(C)c2O1 tf.Tensor([0.01281655], shape=(1,), dtype=float32)
CCCN(CCC)CCc1cccc2c1CC(=O)N2 tf.Tensor([0.99342537], shape=(1,), dtype=float32)
CC(C(=O)c1cccc(c1)Cl)NC(C)(C)C tf.Tensor([0.1379669], shape=(1,), dtype=float32)
CC(=O)N(c1onc(C)c1C)S(=O)(=O)c2ccc(N)cc2 tf.Tensor([1.9473964e-06], shape=(1,), dtype=float32)
CC1=C(N2C(SC1)C(NC(=O)C(N)c3ccccc3)C2=O)C(=O)O tf.Tensor([1.0444643e-05], shape=(1,), dtype=float32)
CC(=O)CC(C1=CC=CC=C1)C1=C(O)C2=C(OC1=O)C=CC=C2 tf.Tensor([0.00060717], shape=(1,), dtype=float32)
CC(C)c1c(C(=O)Nc2ccccc2)c(c3ccccc3)c(c4ccc(F)cc4)n1CCC(O)CC(O)CC(=O)O tf.Tensor([0.04699483], shape=(1,), dtype=float32)
CNC1CCC(c2c1cccc2)c3ccc(c(c3)Cl)Cl tf.Tensor([0.12769073], shape=(1,), dtype=float32)
C(C(Cl)(Cl)Cl)(O)O tf.Tensor([2.037561e-06], shape=(1,), dtype=float32)
CC(=O)C1(O)CCC2C3C=C(C)C4=CC(=O)CCC4(C)C3CCC12C tf.Tensor([0.01968754], shape=(1,), dtype=float32)
CC(C)N1CCC(CC1)N(C(=O)CC1=CC=CC=C1)C1=CC=C(Cl)C=C1 tf.Tensor([0.99710715], shape=(1,), dtype=float32)
CC(C)NCC(O)COc1cccc2cc(oc12)C(=O)C tf.Tensor([0.56310004], shape=(1,), dtype=float32)
OC(COc1cccc2OC(=CC(=O)c12)C(=O)O)COc3cccc4OC(=CC(=O)c34)C(=O)O tf.Tensor([0.00066115], shape=(1,), dtype=float32)
[H][C@]12SC(C)(C)[C@@H](N1C(=O)[C@H]2NC(=O)C(C(O)=O)C1=CC=CC=C1)C(O)=O tf.Tensor([0.00016877], shape=(1,), dtype=float32)
CN1C(CCl)Nc2cc(Cl)c(cc2S1(=O)=O)S(=O)(=O)N tf.Tensor([0.00022956], shape=(1,), dtype=float32)
OC(=O)CC1=CC(Cl)=C(OCC=C)C=C1 tf.Tensor([0.00801694], shape=(1,), dtype=float32)
CCCC(C)C1(CC)C(=O)NC(=S)NC1=O tf.Tensor([0.24097328], shape=(1,), dtype=float32)
OC(=O)C1=CC(=CC=C1O)\N=N\C1=CC=C(C=C1)S(=O)(=O)NC1=NC=CC=C1 tf.Tensor([7.2144525e-05], shape=(1,), dtype=float32)
CN1CCC2=C(C1)C(c3c2cccc3)c4ccccc4 tf.Tensor([0.9885362], shape=(1,), dtype=float32)
CN(C)CCOC(C)(C1=CC=CC=C1)C1=CC=CC=N1 tf.Tensor([0.97200084], shape=(1,), dtype=float32)
CCN1CCCC1CNC(=O)C1=C(OC)C=CC(=C1)S(N)(=O)=O tf.Tensor([0.5377395], shape=(1,), dtype=float32)
OCCN(CCO)c1nc(N2CCCCC2)c3nc(nc(N4CCCCC4)c3n1)N(CCO)CCO tf.Tensor([0.01633438], shape=(1,), dtype=float32)
CCOC(=O)C1=C(C)NC(C)=C(C1C1=C(Cl)C(Cl)=CC=C1)C(=O)OC tf.Tensor([0.00272763], shape=(1,), dtype=float32)
CCCC(CCC)C(O)=O tf.Tensor([0.8200322], shape=(1,), dtype=float32)
CCC(=O)OC(OP(=O)(CCCCc1ccccc1)CC(=O)N2CC(CC2C(=O)O)C3CCCCC3)C(C)C tf.Tensor([0.02228064], shape=(1,), dtype=float32)
C=C1CCC2(C3Cc4ccc(c5c4C2(C1O5)CCN3CC6CC6)O)O tf.Tensor([0.82045597], shape=(1,), dtype=float32)
CC(C)NCC(O)c1cc(O)cc(O)c1 tf.Tensor([0.00073905], shape=(1,), dtype=float32)
CN(C)CCOC(C1=CC=CC=C1)C1=CC=CC=C1 tf.Tensor([0.93778765], shape=(1,), dtype=float32)
c1cc(c2c3c1CC4C5(C3(CCN4CC6CC6)C(O2)C(=O)CC5)O)O tf.Tensor([0.9882933], shape=(1,), dtype=float32)
COc1c(C)c2COC(=O)c2c(O)c1CC=C(C)CCC(=O)OCCN3CCOCC3 tf.Tensor([0.01870375], shape=(1,), dtype=float32)
BrCCC(=O)N1CCN(CC1)C(=O)CCBr tf.Tensor([0.9937255], shape=(1,), dtype=float32)
CCN(CC)C(=O)C1(CC1CN)c2ccccc2 tf.Tensor([0.34901983], shape=(1,), dtype=float32)
NCC1OC(OC2C(O)C(OC3C(O)C(N)CC(N)C3OC4OC(CO)C(O)C(O)C4N)OC2CO)C(N)C(O)C1O tf.Tensor([0.00011027], shape=(1,), dtype=float32)
COC1=CC2=C(C=C1)C=C(C=C2)[C@H](C)C(O)=O tf.Tensor([0.00380735], shape=(1,), dtype=float32)
OC(=O)c1ccccc1OC(=O)c2ccccc2O tf.Tensor([8.791483e-05], shape=(1,), dtype=float32)
CC1=C(C(=O)C(=C(C1=O)OC)OC)CCCCCCCCCCO tf.Tensor([0.00246351], shape=(1,), dtype=float32)
CCCN1CCCCC1C(=O)Nc2c(cccc2C)C tf.Tensor([0.7944549], shape=(1,), dtype=float32)
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CC(Cc1ccc(O)c(O)c1)(NN)C(=O)O tf.Tensor([0.6765121], shape=(1,), dtype=float32)
CC1(C)C(CCC2(C)C1CCC3(C)C2C(=O)C=C4C5CC(C)(CCC5(C)CCC34C)C(=O)O)OC(=O)CCC(=O)O tf.Tensor([0.0103128], shape=(1,), dtype=float32)
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Cc1cc(O)c2ccccc2c1O tf.Tensor([0.00029802], shape=(1,), dtype=float32)
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Cc1ncc2n1c3ccc(cc3C(=NC2)c4ccccc4F)Cl tf.Tensor([0.89928746], shape=(1,), dtype=float32)
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CC(C)CC(CC(=O)O)CN tf.Tensor([0.7932015], shape=(1,), dtype=float32)
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CC(Cc1ccccc1)N tf.Tensor([0.6890452], shape=(1,), dtype=float32)
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Cc1c(scn1)CCCl tf.Tensor([1.], shape=(1,), dtype=float32)
CC(C)(Oc1ccc(cc1)C2CC2(Cl)Cl)C(=O)O tf.Tensor([2.9553014e-06], shape=(1,), dtype=float32)
C[N+](C)(C)CC(O)CC(=O)O tf.Tensor([0.00221156], shape=(1,), dtype=float32)
CC1(OC2COC3(C(C2O1)OC(O3)(C)C)COS(=O)(=O)N)C tf.Tensor([3.2976263e-07], shape=(1,), dtype=float32)
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CN1C(CSCC(F)(F)F)Nc2cc(Cl)c(cc2S1(=O)=O)S(=O)(=O)N tf.Tensor([0.00506863], shape=(1,), dtype=float32)
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CC(CN1c2ccccc2CCc3c1cccc3)CN(C)C tf.Tensor([0.9681478], shape=(1,), dtype=float32)
CC12CCC(=O)C=C1CCC3C4CCC(O)(C(=O)COC(=O)CCC5CCCC5)C4(C)CC(O)C23 tf.Tensor([0.04960962], shape=(1,), dtype=float32)
CCc1cc2c(s1)N(C(=O)CN=C2c3ccccc3Cl)C tf.Tensor([0.9616856], shape=(1,), dtype=float32)
CCOc1nc2cccc(C(=O)OC(C)OC(=O)OC3CCCCC3)c2n1Cc4ccc(cc4)c5ccccc5c6nn[nH]n6 tf.Tensor([0.00856868], shape=(1,), dtype=float32)
CN1CCN2c3ccccc3Cc4ccccc4C2C1 tf.Tensor([0.9829536], shape=(1,), dtype=float32)
CC(C)(C)NCC(O)COc1ccc(NC(=O)NC2CCCCC2)cc1 tf.Tensor([0.10892281], shape=(1,), dtype=float32)
CC(=O)N1CCN(CC1)c2ccc(OCC3COC(Cn4ccnc4)(O3)c5ccc(Cl)cc5Cl)cc2 tf.Tensor([0.13946249], shape=(1,), dtype=float32)
CNC1(CCCCC1=O)C1=CC=CC=C1Cl tf.Tensor([0.58424705], shape=(1,), dtype=float32)
CCOC(=O)C1=C(C)NC(=C(C1c2cccc(Cl)c2Cl)C(=O)OC)C tf.Tensor([0.00272762], shape=(1,), dtype=float32)
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CC1CC2C3CCC(C3(CC(C2C4(C1=CC(=O)C=C4)C)O)C)(C(=O)CO)O tf.Tensor([0.01646548], shape=(1,), dtype=float32)
CCC1(C(=O)NC(=O)N(C1=O)C)c2ccccc2 tf.Tensor([0.9988732], shape=(1,), dtype=float32)
CCCOC(C(=O)OC1CCN(C)CC1)(c2ccccc2)c3ccccc3 tf.Tensor([0.12978198], shape=(1,), dtype=float32)
CCCCc1oc2ccccc2c1C(=O)c3cc(I)c(OCCN(CC)CC)c(I)c3 tf.Tensor([1.4689925e-05], shape=(1,), dtype=float32)
COC1C(CC2CN3CCc4c([nH]c5cc(OC)ccc45)C3CC2C1C(=O)OC)OC(=O)C=Cc6cc(OC)c(OC)c(OC)c6 tf.Tensor([0.00520648], shape=(1,), dtype=float32)
CC(C)(C(=O)O)c1ccc(C(=O)CCCN2CCC(OC(c3ccccc3)c3ccccc3)CC2)cc1 tf.Tensor([0.00228593], shape=(1,), dtype=float32)
CC(C)N1CCC(CC1)N(C(=O)Cc2ccccc2)c3ccc(Cl)cc3 tf.Tensor([0.99710715], shape=(1,), dtype=float32)
CCCCC1C(=O)N(N(C1=O)c2ccccc2)c3ccccc3 tf.Tensor([0.23568991], shape=(1,), dtype=float32)
CC1(C)SC2C(NC(=O)C(N)c3ccc(O)cc3)C(=O)N2C1C(=O)O tf.Tensor([1.4958882e-05], shape=(1,), dtype=float32)
COC(=O)C(N1CCc2sccc2C1)c3ccccc3Cl tf.Tensor([0.01376874], shape=(1,), dtype=float32)
CC(=O)NO tf.Tensor([0.07842369], shape=(1,), dtype=float32)
CCCN1CC(CC2C1Cc3c[nH]c4c3c2ccc4)CSC tf.Tensor([0.9886093], shape=(1,), dtype=float32)
CN(CCCN1c2ccccc2CCc3c1cccc3)CC(=O)c4ccc(cc4)Cl tf.Tensor([0.12834679], shape=(1,), dtype=float32)
[H][C@]12CC3=C(C(O)=C(O)C=C3)C3=CC=CC(CCN1C)=C23 tf.Tensor([0.989802], shape=(1,), dtype=float32)
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CC(Cc1ccccc1)NC tf.Tensor([0.00645473], shape=(1,), dtype=float32)
NCCC(O)(P(=O)(O)O)P(=O)(O)O tf.Tensor([3.5664401e-12], shape=(1,), dtype=float32)
[H][C@@]12CC[C@](O)(C(=O)CO)[C@@]1(C)CC(=O)[C@@]1([H])[C@@]2([H])CCC2=CC(=O)C=C[C@]12C tf.Tensor([0.01083231], shape=(1,), dtype=float32)
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CC12CCC(=O)C=C1CCC3C4CCC(O)(C(=O)CO)C4(C)CC(O)C23 tf.Tensor([0.0108323], shape=(1,), dtype=float32)
CC1C(OCCN1)c2ccccc2 tf.Tensor([0.2771637], shape=(1,), dtype=float32)
CN1CCN(CC1)C2=Nc3ccccc3Sc4c2cc(cc4)Cl tf.Tensor([0.9999341], shape=(1,), dtype=float32)
NC1C2CN(CC12)c3nc4N(C=C(C(=O)O)C(=O)c4cc3F)c5ccc(F)cc5F tf.Tensor([0.00046168], shape=(1,), dtype=float32)
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CN1CCC23CCCCC2C1Cc4c3cc(cc4)O tf.Tensor([0.9867173], shape=(1,), dtype=float32)
c1ccc(cc1)C2C(=O)N=C(O2)N tf.Tensor([0.9718648], shape=(1,), dtype=float32)
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CN1CCCCC1CCN2c3ccccc3Sc4c2cc(cc4)SC tf.Tensor([0.9999951], shape=(1,), dtype=float32)
CCCCCOC(=O)NC1=NC(=O)N(C=C1F)C2OC(C)C(O)C2O tf.Tensor([0.00432024], shape=(1,), dtype=float32)
CC(C)(C)S(=O)(=O)C[C@@H](CC1=CC=CC=C1)C(=O)N[C@@H](CC1=CN=CN1)C(=O)N[C@@H](CC1CCCCC1)[C@@H](O)[C@@H](O)C1CC1 tf.Tensor([0.08897513], shape=(1,), dtype=float32)
CC(C)NCC(O)c1ccc(NS(=O)(=O)C)cc1 tf.Tensor([5.1452633e-07], shape=(1,), dtype=float32)
O=C1OC2=CC=CC=C2C=C1 tf.Tensor([0.00467434], shape=(1,), dtype=float32)
CC(=O)SC1CC2=CC(=O)CCC2(C)C3CCC4(C)C(CCC45CCC(=O)O5)C13 tf.Tensor([0.00108619], shape=(1,), dtype=float32)
CCC1(CCC(C)C)C(=O)NC(=O)NC1=O tf.Tensor([0.98627704], shape=(1,), dtype=float32)
CCN(CC)C(=O)NC1CN(C2Cc3c[nH]c4c3c(ccc4)C2=C1)C tf.Tensor([0.01829495], shape=(1,), dtype=float32)
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OCC1OC(CC1O)N2C=C(C=CBr)C(=O)NC2=O tf.Tensor([0.00357127], shape=(1,), dtype=float32)
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OC(=O)C(S)C(S)C(=O)O tf.Tensor([4.6376292e-07], shape=(1,), dtype=float32)
OC(=O)c1cc(ccc1O)N=Nc2ccc(O)c(c2)C(=O)O tf.Tensor([0.00268602], shape=(1,), dtype=float32)
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CCOc1ccccc1OC(c2ccccc2)C3CNCCO3 tf.Tensor([0.01962304], shape=(1,), dtype=float32)
CCOC(=O)C1=C(C)NC(=C(C1c2ccccc2C=CC(=O)OC(C)(C)C)C(=O)OCC)C tf.Tensor([0.01180196], shape=(1,), dtype=float32)
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Cc1cccc(OCC(O)CNC(C)C)c1 tf.Tensor([0.02131734], shape=(1,), dtype=float32)
CCC(Cc1c(I)cc(I)c(N)c1I)C(=O)O tf.Tensor([6.3840384e-06], shape=(1,), dtype=float32)
ClC1=CC=CC(Cl)=C1NC1=NCCN1 tf.Tensor([0.03207919], shape=(1,), dtype=float32)
CCC(C)(C)C(=O)OC1CC(C)C=C2C=CC(C)C(CCC3CC(O)CC(=O)O3)C12 tf.Tensor([0.00259872], shape=(1,), dtype=float32)
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CCc1nc(N)nc(N)c1c2ccc(Cl)cc2 tf.Tensor([0.00931503], shape=(1,), dtype=float32)
CN(CCOc1ccc(NS(=O)(=O)C)cc1)CCc2ccc(NS(=O)(=O)C)cc2 tf.Tensor([0.00026094], shape=(1,), dtype=float32)
CN(C)CC(c1ccc(cc1)OC)C2(CCCCC2)O tf.Tensor([0.19083741], shape=(1,), dtype=float32)
CCOC(=O)C(CCc1ccccc1)NC(C)C(=O)N2C3CCCCC3CC2C(=O)O tf.Tensor([0.0054875], shape=(1,), dtype=float32)
CCCCCCCCCCCCCCCC(=O)OCC(NC(=O)C(Cl)Cl)C(O)c1ccc(cc1)[N+](=O)[O] tf.Tensor([0.0629271], shape=(1,), dtype=float32)
CCC(=C(CC)c1ccc(O)cc1)c2ccc(O)cc2 tf.Tensor([0.00453754], shape=(1,), dtype=float32)
CC(C)C(NC(=O)N(C)Cc1csc(n1)C(C)C)C(=O)NC(CC(O)C(Cc2ccccc2)NC(=O)OCc3cncs3)Cc4ccccc4 tf.Tensor([0.27363333], shape=(1,), dtype=float32)
CC(C(c1ccc(cc1)O)O)N2CCC(CC2)Cc3ccccc3 tf.Tensor([0.2934399], shape=(1,), dtype=float32)
Cc1ncc([N+](=O)[O])n1CCO tf.Tensor([1.0253808e-05], shape=(1,), dtype=float32)
CCN1CCCC1CNC(=O)c2cc(ccc2OC)S(=O)(=O)N tf.Tensor([0.5377396], shape=(1,), dtype=float32)
OC1(CCN(CCCC(=O)C2=CC=C(F)C=C2)CC1)C1=CC=C(Cl)C=C1 tf.Tensor([0.987715], shape=(1,), dtype=float32)
NNc1nncc2ccccc12 tf.Tensor([0.9229113], shape=(1,), dtype=float32)
NC(Cc1ccc(cc1)N(CCCl)CCCl)C(=O)O tf.Tensor([0.01727365], shape=(1,), dtype=float32)
CCN(CCO)CCn1c(Cc2ccccc2)nc3N(C)C(=O)N(C)C(=O)c13 tf.Tensor([0.13137706], shape=(1,), dtype=float32)
C1CN=C(NC(C2CC2)C3CC3)O1 tf.Tensor([0.25490648], shape=(1,), dtype=float32)
COC(=O)Nc1nc2cc(ccc2[nH]1)C(=O)c3ccccc3 tf.Tensor([0.02910578], shape=(1,), dtype=float32)
OCC(CO)NC1CC(O)(CO)C(O)C(O)C1O tf.Tensor([0.0005298], shape=(1,), dtype=float32)
c1cc(ccc1N2CCCCS2(=O)=O)S(=O)(=O)N tf.Tensor([1.6458994e-08], shape=(1,), dtype=float32)
CCOc1cc(CC(=O)NC(CC(C)C)c2ccccc2N3CCCCC3)ccc1C(=O)O tf.Tensor([0.19603941], shape=(1,), dtype=float32)
CC1(C)SC2C(NC(=O)C(N)c3ccccc3)C(=O)N2C1C(=O)OCOC(=O)C4N5C(CC5=O)S(=O)(=O)C4(C)C tf.Tensor([4.89113e-05], shape=(1,), dtype=float32)
C[N+]1(C)CCCC(C1)OC(=O)C(O)(c2ccccc2)c3ccccc3 tf.Tensor([0.00068355], shape=(1,), dtype=float32)
Nc1nc(NC2CC2)c3ncn(C4CC(CO)C=C4)c3n1 tf.Tensor([0.00023947], shape=(1,), dtype=float32)
N#Cc1ccc(cc1)C(c2ccc(cc2)C#N)n3cncn3 tf.Tensor([0.02378875], shape=(1,), dtype=float32)
CC(C)CC1Nc2cc(Cl)c(cc2S(=O)(=O)N1)S(=O)(=O)N tf.Tensor([0.00221012], shape=(1,), dtype=float32)
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CC(C)C1CCC(CC1)C(=O)NC(Cc2ccccc2)C(=O)O tf.Tensor([0.00747692], shape=(1,), dtype=float32)
CCOC(=O)c1c(CSc2ccccc2)n(C)c3cc(Br)c(O)c(CN(C)C)c13 tf.Tensor([0.50839704], shape=(1,), dtype=float32)
CN1CCN(CC1)CCCN2c3ccccc3Sc4c2cc(cc4)C(F)(F)F tf.Tensor([0.9984755], shape=(1,), dtype=float32)
CNC(C)C(O)c1ccc(O)cc1 tf.Tensor([0.9770809], shape=(1,), dtype=float32)
CCCCC1=NC2(CCCC2)C(=O)N1Cc3ccc(cc3)c4ccccc4c5nnn[nH]5 tf.Tensor([0.2791582], shape=(1,), dtype=float32)
CC(=CC=CC(=CC(=O)O)C)C=CC1=C(C)CCCC1(C)C tf.Tensor([0.0186278], shape=(1,), dtype=float32)
CCC(=O)c1ccc2c(c1)N(c3ccccc3S2)CCCN4CCN(CC4)CCO tf.Tensor([0.99993616], shape=(1,), dtype=float32)
CCOC(=O)C(CCc1ccccc1)NC2CCc3ccccc3N(CC(=O)O)C2=O tf.Tensor([0.00805132], shape=(1,), dtype=float32)
CCOC(=O)c1ccc(N)cc1 tf.Tensor([1.3322311e-05], shape=(1,), dtype=float32)
CN(C)CCc1c[nH]c2c1cc(cc2)Cn3cncn3 tf.Tensor([0.13865061], shape=(1,), dtype=float32)
[H][C@@]1(CC[C@@]2([H])[C@]3([H])CCC4=CC(=O)CC[C@]4(C)[C@@]3([H])[C@@]([H])(O)C[C@]12C)C(=O)CO tf.Tensor([0.00320079], shape=(1,), dtype=float32)
CC(N)C(=O)Nc1c(C)cccc1C tf.Tensor([0.00491196], shape=(1,), dtype=float32)
CN(C)CCC=C1C=C2C=CC=CC2=Cc3ccccc13 tf.Tensor([0.93243104], shape=(1,), dtype=float32)
CCN(CC)Cc1cc(Nc2ccnc3cc(Cl)ccc23)ccc1O tf.Tensor([0.5436411], shape=(1,), dtype=float32)
CCC1OC(=O)C(C)C(OC2CC(C)(OC)C(O)C(C)O2)C(C)C(OC3OC(C)CC(C3O)N(C)C)C(C)(O)CC(C)C4NC(COCCOC)OC(C4C)C1(C)O tf.Tensor([0.00913135], shape=(1,), dtype=float32)
NCC1OC(OC2C(N)CC(N)C(OC3OC(CO)C(O)C(N)C3O)C2O)C(O)C(O)C1O tf.Tensor([4.418122e-07], shape=(1,), dtype=float32)
[H][C@@]1(CC[C@]2(O)[C@]3([H])CCC4=C[C@]([H])(CC[C@]4(C)[C@@]3([H])CC[C@]12C)O[C@]1([H])O[C@@]([H])(C)[C@]([H])(O)[C@@]([H])(O)[C@@]1([H])O)C1=COC(=O)C=C1 tf.Tensor([0.0021567], shape=(1,), dtype=float32)
CCCN(CCC)C(=O)C(CCC(=O)O)NC(=O)c1ccccc1 tf.Tensor([0.7263891], shape=(1,), dtype=float32)
CN(C)c1nc(nc(n1)N(C)C)N(C)C tf.Tensor([0.00632749], shape=(1,), dtype=float32)
OC(=O)C1=CC=CC=C1O tf.Tensor([3.281636e-05], shape=(1,), dtype=float32)
COc1ccc2c(c1)c(CC(=O)OCC=C(C)CCC=C(C)CCC=C(C)C)c(C)n2C(=O)c3ccc(Cl)cc3 tf.Tensor([0.01561445], shape=(1,), dtype=float32)
CN(C)CCC=C1c2ccccc2CCc2ccccc21 tf.Tensor([0.93243104], shape=(1,), dtype=float32)
CS(=O)(=O)c1ccc(cc1)C(O)C(CO)NC(=O)C(Cl)Cl tf.Tensor([1.3407058e-06], shape=(1,), dtype=float32)
Cc1c(OCC(F)(F)F)ccnc1CS(=O)c2nc3ccccc3[nH]2 tf.Tensor([0.00639111], shape=(1,), dtype=float32)
COc1cc(ccc1Cc2cn(C)c3ccc(NC(=O)OC4CCCC4)cc23)C(=O)NS(=O)(=O)c5ccccc5C tf.Tensor([0.01347689], shape=(1,), dtype=float32)
CC(C)(C)NC(=O)C1CCC2C3CCC4NC(=O)C=CC4(C)C3CCC12C tf.Tensor([0.06887438], shape=(1,), dtype=float32)
CN(C)C1C2C(O)C3C(=C)c4cccc(O)c4C(=O)C3=C(O)C2(O)C(=O)C(=C1O)C(=O)N tf.Tensor([0.00041567], shape=(1,), dtype=float32)
CC(C)CN(CC(OP(=O)(O)O)C(Cc1ccccc1)NC(=O)OC2CCOC2)S(=O)(=O)c3ccc(N)cc3 tf.Tensor([1.2682555e-05], shape=(1,), dtype=float32)
CNNCc1ccc(cc1)C(=O)NC(C)C tf.Tensor([0.006551], shape=(1,), dtype=float32)
c1ccc(cc1)C2=NCc3nncn3c4c2cc(cc4)Cl tf.Tensor([0.99886733], shape=(1,), dtype=float32)
Cn1c2c(c(=O)n(c1=O)C)nc[nH]2 tf.Tensor([0.9723088], shape=(1,), dtype=float32)
ClC(Cl)C(c1ccc(Cl)cc1)c2ccccc2Cl tf.Tensor([0.6866068], shape=(1,), dtype=float32)
NS(=O)(=O)C1=C(Cl)C=C(NCC2=CC=CO2)C(=C1)C(O)=O tf.Tensor([6.943611e-08], shape=(1,), dtype=float32)
c1cc(c2c3c1CC4C5(C3(CCN4CC6CCC6)C(O2)C(CC5)O)O)O tf.Tensor([0.98577964], shape=(1,), dtype=float32)
COc1ccc(cc1)C(=O)Nc2ccccc2C(C)CN3CCCCC3 tf.Tensor([0.30065727], shape=(1,), dtype=float32)
c1ccc2c(c1)CCc3ccccc3N2CCCN4CCC(CC4)(C(=O)N)N5CCCCC5 tf.Tensor([0.9984643], shape=(1,), dtype=float32)
CCC1(O)CCC2C3CCC4=CCCCC4C3CCC12C tf.Tensor([0.133834], shape=(1,), dtype=float32)
CNCCC=C1c2ccccc2CCc3c1cccc3 tf.Tensor([0.9507633], shape=(1,), dtype=float32)
Cc1cccc(C)c1NC(=O)CN2CCN(CCCC(c3ccc(F)cc3)c4ccc(F)cc4)CC2 tf.Tensor([0.7844297], shape=(1,), dtype=float32)
CCOC(=O)C1(CCN(C)CC1)C1=CC=CC=C1 tf.Tensor([0.9973297], shape=(1,), dtype=float32)
CN(C)CCCN1C2=CC=CC=C2SC2=CC=CC=C12 tf.Tensor([0.99998844], shape=(1,), dtype=float32)
NC1=NC(=O)N(C=C1)C2CCC(CO)O2 tf.Tensor([0.01079087], shape=(1,), dtype=float32)
NC(=O)CCC1NC(=O)C(Cc2ccccc2)NC(=O)C(Cc3ccc(O)cc3)NC(=O)CCSSCC(NC(=O)C(CC(=O)N)NC1=O)C(=O)N4CCCC4C(=O)NC(CCCNC(=N)N)C(=O)NCC(=O)N tf.Tensor([0.00312868], shape=(1,), dtype=float32)
CCCc1nc(c(C(=O)OCC2=C(C)OC(=O)O2)n1Cc3ccc(cc3)c4ccccc4c5nnn[nH]5)C(C)(C)O tf.Tensor([0.00668463], shape=(1,), dtype=float32)
Nc1n[n+]([O])c2ccccc2[n+]1[O] tf.Tensor([0.08981838], shape=(1,), dtype=float32)
c1ccc2c(c1)/C(=C\CCN3CCN(CC3)CCO)/c4cc(ccc4S2)C(F)(F)F tf.Tensor([0.99677485], shape=(1,), dtype=float32)
NC1=NC(=O)NC=C1F tf.Tensor([3.7145574e-07], shape=(1,), dtype=float32)
CC(C)CC1CN2CCc3cc(c(cc3C2CC1=O)OC)OC tf.Tensor([0.48529735], shape=(1,), dtype=float32)
CC1(O)CCC2C3CCC4CC(=O)OCC4(C)C3CCC12C tf.Tensor([0.01631601], shape=(1,), dtype=float32)
OC(=O)c1cc(ccc1O)N=Nc2ccc(cc2)S(=O)(=O)Nc3ccccn3 tf.Tensor([7.214446e-05], shape=(1,), dtype=float32)
NC1=NC(=O)c2nc(CNc3ccc(cc3)C(=O)NC(CCC(=O)O)C(=O)O)cnc2N1 tf.Tensor([1.0456263e-05], shape=(1,), dtype=float32)
CC1Nc2cc(Cl)c(cc2C(=O)N1c3ccccc3C)S(=O)(=O)N tf.Tensor([0.00252297], shape=(1,), dtype=float32)
CC(C)N=C1C=C2N(c3ccc(Cl)cc3)c4ccccc4N=C2C=C1Nc5ccc(Cl)cc5 tf.Tensor([0.9963067], shape=(1,), dtype=float32)
CC(C(=O)O)c1ccc(s1)C(=O)c2ccccc2 tf.Tensor([0.00232865], shape=(1,), dtype=float32)
CC(C(=O)O)c1cccc(Oc2ccccc2)c1 tf.Tensor([0.00013557], shape=(1,), dtype=float32)
Nc1ccc(cc1)S(=O)(=O)Nc2ncccn2 tf.Tensor([2.0543007e-07], shape=(1,), dtype=float32)
OC(=O)COCCN1CCN(CC1)C(C1=CC=CC=C1)C1=CC=C(Cl)C=C1 tf.Tensor([0.06481011], shape=(1,), dtype=float32)
c1ccc(cc1)C2=NCC(=O)N(c3c2cc(cc3)Cl)CC4CC4 tf.Tensor([0.99950314], shape=(1,), dtype=float32)
CNC(=NC)NCc1ccccc1 tf.Tensor([0.22309887], shape=(1,), dtype=float32)
CCN(CC)CCNC(=O)c1ccc(N)cc1 tf.Tensor([0.0660698], shape=(1,), dtype=float32)
COC1CC(CCC1O)C=C(C)C2OC(=O)C3CCCCN3C(=O)C(=O)C4(O)OC(C(CC(C)CC(=CC(CC=C)C(=O)CC(O)C2C)C)OC)C(CC4C)OC tf.Tensor([0.03211036], shape=(1,), dtype=float32)
CC(=O)Oc1ccc(cc1)C(c2ccc(OC(=O)C)cc2)c3ccccn3 tf.Tensor([0.20805508], shape=(1,), dtype=float32)
Oc1ccc(cc1)C2(OC(=O)c3ccccc23)c4ccc(O)cc4 tf.Tensor([0.9931008], shape=(1,), dtype=float32)
COc1ccc(CCN(C)CCCN2CCc3cc(OC)c(OC)cc3CC2=O)cc1OC tf.Tensor([0.14201398], shape=(1,), dtype=float32)
CCCN1CC(CC2C1Cc3cccc(c3C2)O)NS(=O)(=O)N(CC)CC tf.Tensor([0.9538706], shape=(1,), dtype=float32)
C1C2CC3CC1CC(C2)(C3)N tf.Tensor([0.6055917], shape=(1,), dtype=float32)
CCC(C1=C(O)Oc2ccccc2C1=O)c3ccccc3 tf.Tensor([0.00199891], shape=(1,), dtype=float32)
OCC(O)C(O)C(OC1OC(CO)C(O)C(O)C1O)C(O)CO tf.Tensor([1.1002106e-06], shape=(1,), dtype=float32)
OC(CCN1CCCC1)(C1CCCCC1)C1=CC=CC=C1 tf.Tensor([0.96299314], shape=(1,), dtype=float32)
NC(=O)NO tf.Tensor([0.3201743], shape=(1,), dtype=float32)
CCOC(=O)C1=CC(OC(CC)CC)C(NC(=O)C)C(N)C1 tf.Tensor([0.01603842], shape=(1,), dtype=float32)
CCOC(=O)C=C(C)C=CC=C(C)C=Cc1c(C)cc(OC)c(C)c1C tf.Tensor([0.01882659], shape=(1,), dtype=float32)
[O][N+](=O)OCC(CO[N+](=O)[O])O[N+](=O)[O] tf.Tensor([0.00021028], shape=(1,), dtype=float32)
CC(C)(Oc1ccc(Cl)cc1)C(=O)O tf.Tensor([0.0002943], shape=(1,), dtype=float32)
CN1N=C(SC1=NC(=O)C)S(=O)(=O)N tf.Tensor([0.7930073], shape=(1,), dtype=float32)
CCN(CC)CCN1c2ccc(cc2C(=NCC1=O)c3ccccc3F)Cl tf.Tensor([0.99096], shape=(1,), dtype=float32)
CN1CCCN=C1C=Cc2cccs2 tf.Tensor([0.10526799], shape=(1,), dtype=float32)
CC12CCC3C(CCC4=CC(=O)CCC34)C1CCC2(O)C#C tf.Tensor([0.02645089], shape=(1,), dtype=float32)
CC(C)n1c(C=CC(O)CC(O)CC(=O)O)c(c2ccc(F)cc2)c3ccccc13 tf.Tensor([0.07400096], shape=(1,), dtype=float32)
CCCC1OC2CC3C4CCC5=CC(=O)C=CC5(C)C4C(O)CC3(C)C2(O1)C(=O)CO tf.Tensor([0.00056449], shape=(1,), dtype=float32)
C[N+]1(C)CCC(=C(c2ccccc2)c3ccccc3)CC1 tf.Tensor([0.97810715], shape=(1,), dtype=float32)
c1ccc(c(c1)C2=NC(C(=O)N(c3c2cc(cc3)Cl)CCC#N)O)F tf.Tensor([0.97507423], shape=(1,), dtype=float32)
CCNC(=O)N(CCCN(C)C)C(=O)C1CC2c3cccc4c3c(c[nH]4)CC2N(C1)CC=C tf.Tensor([0.6165563], shape=(1,), dtype=float32)
CNC(CC(C)C)C(=O)NC1C(O)c2ccc(Oc3cc4cc(Oc5ccc(cc5Cl)C(O)C6CC(=O)C(NC(=O)C4NC(=O)C(CC(=O)N)NC1=O)c7ccc(O)c(c7)c8c(O)cc(O)cc8C(NC6=O)C(=O)O)c3OC9OC(CO)C(O)C(O)C9OC%10CC(C)(N)C(O)C(C)O%10)c(Cl)c2 tf.Tensor([0.00232265], shape=(1,), dtype=float32)
CN1CCN(CC(=O)N2c3ccccc3C(=O)Nc4cccnc24)CC1 tf.Tensor([0.01138007], shape=(1,), dtype=float32)
COc1ccc(cc1)C(=C(CCC(=O)O)C#N)c2ccc(OC)cc2 tf.Tensor([0.00162111], shape=(1,), dtype=float32)
c1ccc2c(c1)[nH]c(=O)n2C3CCN(CC3)CCCC(c4ccc(cc4)F)c5ccc(cc5)F tf.Tensor([0.63280696], shape=(1,), dtype=float32)
CCC1(C(=O)N(C(=O)N1)C)c2ccccc2 tf.Tensor([0.9999149], shape=(1,), dtype=float32)
c1cnc(nc1)N2CCN(CC2)CCCCN3C(=O)CC4(CCCC4)CC3=O tf.Tensor([0.96823907], shape=(1,), dtype=float32)
COC1=CC=C(CCN2CCC(CC2)NC2=NC3=CC=CC=C3N2CC2=CC=C(F)C=C2)C=C1 tf.Tensor([0.05628369], shape=(1,), dtype=float32)
CC(C)CC(C1(CCC1)c2ccc(cc2)Cl)N(C)C tf.Tensor([0.76866895], shape=(1,), dtype=float32)
CC1=Nc2ccc(Cl)cc2S(=O)(=O)N1 tf.Tensor([0.9980964], shape=(1,), dtype=float32)
CC(NC(=NC#N)Nc1ccncc1)C(C)(C)C tf.Tensor([3.6478289e-06], shape=(1,), dtype=float32)
CC(Cc1cccc(c1)C(F)(F)F)NCCOC(=O)c2ccccc2 tf.Tensor([0.23543102], shape=(1,), dtype=float32)
CN1CCN=C(c2c1ccc(c2)Cl)c3ccccc3 tf.Tensor([0.9988072], shape=(1,), dtype=float32)
CC1(C)SC2C(NC(=O)C(C(=O)Oc3ccc4CCCc4c3)c5ccccc5)C(=O)N2C1C(=O)O tf.Tensor([0.0005942], shape=(1,), dtype=float32)
CC(=CCCC(=CCCC(=CCCC(=CCC1=C(C)C(=O)c2ccccc2C1=O)C)C)C)C tf.Tensor([0.03993833], shape=(1,), dtype=float32)
CC(C[N+](C)(C)C)OC(=O)N tf.Tensor([0.99921674], shape=(1,), dtype=float32)
COc1ccc2c(c1)C(=O)N(CCc3ccc(cc3)S(=O)(=O)NC(=O)NC4CCCCC4)C(=O)C2(C)C tf.Tensor([0.00057319], shape=(1,), dtype=float32)
CC1OC(CC(O)C1O)OC2C(O)CC(OC3C(O)CC(OC4CCC5(C)C(CCC6C5CC(O)C7(C)C(CCC67O)C8=CC(=O)OC8)C4)OC3C)OC2C tf.Tensor([0.00021285], shape=(1,), dtype=float32)
CN1CCCCC1CCN2c3ccccc3Sc4c2cc(cc4)S(=O)C tf.Tensor([0.9999896], shape=(1,), dtype=float32)
CNCCCN1c2ccccc2CCc3c1cccc3 tf.Tensor([0.9647321], shape=(1,), dtype=float32)
CC1CC(CC(C)(C)C1)OC(=O)C(O)c2ccccc2 tf.Tensor([0.00163304], shape=(1,), dtype=float32)
COC(=O)C1=C(C)NC(=C(C1c2cccc(c2)[N+](=O)[O])C(=O)OC(C)(C)CN(C)CCC(c3ccccc3)c4ccccc4)C tf.Tensor([0.5077823], shape=(1,), dtype=float32)
CN1CCN(CC1)C2=Nc3ccccc3Oc4c2cc(cc4)Cl tf.Tensor([0.9010825], shape=(1,), dtype=float32)
COC1=CC=C(C=C1)[C@@H]1SC2=C(C=CC=C2)N(CCN(C)C)C(=O)[C@@H]1OC(C)=O tf.Tensor([0.7454437], shape=(1,), dtype=float32)
FC(F)(F)C1(OC(=O)Nc2ccc(Cl)cc12)C#CC3CC3 tf.Tensor([0.93626577], shape=(1,), dtype=float32)
CC(C)(C)NC(=O)C1CC2CCCCC2CN1CC(O)C(Cc3ccccc3)NC(=O)C(CC(=O)N)NC(=O)c4ccc5ccccc5n4 tf.Tensor([0.01091727], shape=(1,), dtype=float32)
[H][C@@]12CC[C@](O)(C(=O)CO)[C@@]1(C)C[C@H](O)[C@@]1([H])[C@@]2([H])CCC2=CC(=O)C=C[C@]12C tf.Tensor([0.01083231], shape=(1,), dtype=float32)
CCNC(C)Cc1cccc(c1)C(F)(F)F tf.Tensor([0.00550115], shape=(1,), dtype=float32)
CC(=O)SCC(Cc1ccccc1)C(=O)NCC(=O)OCc2ccccc2 tf.Tensor([0.00238343], shape=(1,), dtype=float32)
c1cc(ccc1C(CC(=O)O)CN)Cl tf.Tensor([0.6185569], shape=(1,), dtype=float32)
CCc1c([nH]c2c1C(=O)C(CC2)CN3CCOCC3)C tf.Tensor([0.15773723], shape=(1,), dtype=float32)
CN1C(S(=O)(=O)CCC1=O)c2ccc(cc2)Cl tf.Tensor([0.6087034], shape=(1,), dtype=float32)
OC1=C(CC2=C(O)c3ccccc3OC2=O)C(=O)Oc4ccccc14 tf.Tensor([5.1497922e-05], shape=(1,), dtype=float32)
CC(=O)Nc1ccc(OC(=O)c2ccccc2OC(=O)C)cc1 tf.Tensor([0.04776736], shape=(1,), dtype=float32)
c1ccc2c(c1)N(c3cc(ccc3S2)C#N)CCCN4CCC(CC4)O tf.Tensor([0.9657489], shape=(1,), dtype=float32)
Nc1ccc(N=Nc2ccccc2)c(N)n1 tf.Tensor([0.7908625], shape=(1,), dtype=float32)
c1ccc2c(c1)C(=Nc3ccccc3S2)N4CCN(CC4)CCOCCO tf.Tensor([0.99991816], shape=(1,), dtype=float32)
COC1CC(OC2C(C)C(OC3OC(C)CC(C3OC(=O)C)N(C)C)C(C)CC4(CO4)C(=O)C(C)C(OC(=O)C)C(C)C(C)OC(=O)C2C)OC(C)C1OC(=O)C tf.Tensor([0.02377352], shape=(1,), dtype=float32)
COc1cc(NC(C)CCCN)c2ncccc2c1 tf.Tensor([0.59314865], shape=(1,), dtype=float32)
c1ccc(c(c1)C2=NCC(=O)Nc3c2cc(cc3)[N+](=O)[O])Cl tf.Tensor([0.9806977], shape=(1,), dtype=float32)
CCCc1nc2c(C)cc(cc2n1Cc3ccc(cc3)c4ccccc4C(=O)O)c5nc6ccccc6n5C tf.Tensor([0.87132514], shape=(1,), dtype=float32)
Cc1[nH]cnc1CN2CCc3c(C2=O)c4ccccc4n3C tf.Tensor([0.91390187], shape=(1,), dtype=float32)
CN1CCCN=C1COC(=O)C(O)(C2CCCCC2)c3ccccc3 tf.Tensor([0.00078834], shape=(1,), dtype=float32)
CC1(C)NC(=O)N(C1=O)c2ccc(c(c2)C(F)(F)F)[N+](=O)[O] tf.Tensor([0.40029243], shape=(1,), dtype=float32)
[O][N+](=O)c1oc(C=NN2CC(=O)NC2=O)cc1 tf.Tensor([0.2086697], shape=(1,), dtype=float32)
CN1CCC23CCCCC2C1Cc4c3cc(cc4)OC tf.Tensor([0.98013496], shape=(1,), dtype=float32)
CCOC(=O)Nc1ccc2Sc3ccccc3N(C(=O)CCN4CCOCC4)c2c1 tf.Tensor([0.8919635], shape=(1,), dtype=float32)
Cc1ccc(cc1)C(=O)c2cc(c(c(c2)O)O)[N+](=O)[O] tf.Tensor([0.7330187], shape=(1,), dtype=float32)
CNC(=C[N+](=O)[O])NCCSCc1csc(CN(C)C)n1 tf.Tensor([0.00021279], shape=(1,), dtype=float32)
CCOC(=O)C(C)(C)Oc1ccc(Cl)cc1 tf.Tensor([0.00012785], shape=(1,), dtype=float32)
CCC1OC(=O)C(C)C(OC2CC(C)(OC)C(O)C(C)O2)C(C)C(OC3OC(C)CC(C3O)N(C)C)C(C)(CC(C)C(=O)C(C)C(O)C1(C)O)OC tf.Tensor([0.00554489], shape=(1,), dtype=float32)
CCN(c1cccc(c1)c2ccnc3n2ncc3C#N)C(=O)C tf.Tensor([0.80753], shape=(1,), dtype=float32)
CNC(=C[N+](=O)[O])NCCSCc1oc(CN(C)C)cc1 tf.Tensor([0.00232279], shape=(1,), dtype=float32)
Nc1ccc(cc1)S(=O)(=O)Nc2ccccn2 tf.Tensor([0.00011257], shape=(1,), dtype=float32)
CCOc1ccccc1OCC2CNCCO2 tf.Tensor([0.06558139], shape=(1,), dtype=float32)
CN(C)CC\C=C1\C2=CC=CC=C2SC2=CC=C(Cl)C=C12 tf.Tensor([0.9999504], shape=(1,), dtype=float32)
CC(C)(C)NCC(O)COC1=CC=CC2=C1C[C@H](O)[C@H](O)C2 tf.Tensor([0.7216593], shape=(1,), dtype=float32)
CC(=O)c1ccc2c(c1)N(c3ccccc3S2)CCCN4CCC(CC4)CCO tf.Tensor([0.83119744], shape=(1,), dtype=float32)
C=CCN1CCC23c4c5ccc(c4OC2C(=O)CCC3(C1C5)O)O tf.Tensor([0.99541944], shape=(1,), dtype=float32)
NS(=O)(=O)c1cc2C(=O)NC(Nc2cc1Cl)c3ccccc3 tf.Tensor([0.00106162], shape=(1,), dtype=float32)
CCC12CCC3C(CCC4=CC(=O)CCC34)C1CCC2(O)C#C tf.Tensor([0.04573907], shape=(1,), dtype=float32)
Cc1c(C(=O)O)c2cc(F)ccc2nc1c3ccc(cc3)c4ccccc4F tf.Tensor([0.8434261], shape=(1,), dtype=float32)
FC(F)(F)c1cccc(Nc2ncccc2C(=O)OCCN3CCOCC3)c1 tf.Tensor([0.02321039], shape=(1,), dtype=float32)
NCCS tf.Tensor([0.9965579], shape=(1,), dtype=float32)
Cc1cc2N=C3C(=O)NC(=O)N=C3N(CC(O)C(O)C(O)CO)c2cc1C tf.Tensor([0.00048298], shape=(1,), dtype=float32)
CC(C)CCCC(C)CCCC(C)CCCC(=CCC1=C(C)C(=O)c2ccccc2C1=O)C tf.Tensor([0.03993835], shape=(1,), dtype=float32)
c1ccc(cc1)C2=NCC(=O)N(c3c2cc(cc3)Cl)CC(F)(F)F tf.Tensor([0.9519635], shape=(1,), dtype=float32)
OC(=O)c1ccccc1Nc2cccc(c2)C(F)(F)F tf.Tensor([0.00267858], shape=(1,), dtype=float32)
CC(=CC=CC=C(C)C=CC=C(C)C=CC1=C(C)CCCC1(C)C)C=CC=C(C)C=CC2=C(C)CCCC2(C)C tf.Tensor([0.28921002], shape=(1,), dtype=float32)
CC(=O)c1ccc2c(c1)N(c3ccccc3S2)CCCN4CCN(CC4)CCO tf.Tensor([0.999724], shape=(1,), dtype=float32)
CC(C)(C)NC[C@H](O)COC1=CC=CC=C1C1CCCC1 tf.Tensor([0.4523451], shape=(1,), dtype=float32)
COCC(=O)O[C@]1(CCN(C)CCCC2=NC3=CC=CC=C3N2)CCC2=C(C=CC(F)=C2)[C@@H]1C(C)C tf.Tensor([0.5458893], shape=(1,), dtype=float32)
Cc1onc(c1C(=O)NC2C3SC(C)(C)C(N3C2=O)C(=O)O)c4c(F)cccc4Cl tf.Tensor([0.06989069], shape=(1,), dtype=float32)
CCC12CCCN3CCc4c(C13)n(c5ccccc45)C(O)(C2)C(=O)OC tf.Tensor([0.54569715], shape=(1,), dtype=float32)
CN(C)CC/C=C\1/c2ccccc2COc3c1cccc3 tf.Tensor([0.99315953], shape=(1,), dtype=float32)
CCCNC1CCc2c(sc(n2)N)C1 tf.Tensor([0.9992165], shape=(1,), dtype=float32)
c1ccc2c(c1)C=Cc3ccccc3N2C(=O)N tf.Tensor([0.8680433], shape=(1,), dtype=float32)
CCNCc1c(CSC)cnc(C)c1O tf.Tensor([1.9389847e-06], shape=(1,), dtype=float32)
CCN1C=C(C(=O)O)C(=O)c2cnc(nc12)N3CCNCC3 tf.Tensor([0.00680451], shape=(1,), dtype=float32)
CCN(CC)C(=S)SSC(=S)N(CC)CC tf.Tensor([6.206987e-07], shape=(1,), dtype=float32)
Nc1nc(cs1)C(=NO)C(=O)NC2C3SCC(=C(N3C2=O)C(=O)O)C=C tf.Tensor([0.00020546], shape=(1,), dtype=float32)
COC1CN(CCCOc2ccc(F)cc2)CCC1NC(=O)c3cc(Cl)c(N)cc3OC tf.Tensor([0.11396591], shape=(1,), dtype=float32)
[H][C@@]12C[C@@H](C)[C@](O)(C(=O)CO)[C@@]1(C)C[C@H](O)[C@@]1(F)[C@@]2([H])CCC2=CC(=O)C=C[C@]12C tf.Tensor([0.9514988], shape=(1,), dtype=float32)
CCOC(=O)c1c2n(cn1)c3ccc(cc3C(=O)N(C2)C)F tf.Tensor([0.02608612], shape=(1,), dtype=float32)
CC(S)C(=O)NCC(=O)O tf.Tensor([1.5284084e-07], shape=(1,), dtype=float32)
CC12CC(O)C3(F)C(CCC4=CC(=O)CCC34C)C1CCC2(O)C(=O)CO tf.Tensor([0.18191321], shape=(1,), dtype=float32)
C1CNCCN1 tf.Tensor([0.75546473], shape=(1,), dtype=float32)
c1ccc2c(c1)C(=O)N(C2=O)C3CCC(=O)NC3=O tf.Tensor([0.4669433], shape=(1,), dtype=float32)
CN1CCC(=C2c3ccccc3CCc4c2nccc4)CC1 tf.Tensor([0.97262603], shape=(1,), dtype=float32)
CCCCCc1cc(c2c(c1)OC(C3C2C=C(CC3)C)(C)C)O tf.Tensor([0.09489223], shape=(1,), dtype=float32)
NC(=NCC1COC2(CCCCC2)O1)N tf.Tensor([1.5207579e-05], shape=(1,), dtype=float32)
OC(=O)CCCN1CCC(CC1)OC(c2ccc(Cl)cc2)c3ccccn3 tf.Tensor([0.00680007], shape=(1,), dtype=float32)
CN1CCCC1c2cccnc2 tf.Tensor([0.40468508], shape=(1,), dtype=float32)
CCN(CC)CCNC(=O)c1ccc(NS(=O)(=O)C)cc1 tf.Tensor([5.325394e-05], shape=(1,), dtype=float32)
c1ccc(cc1)C(CCN2CCCCC2)(C3CC4CC3C=C4)O tf.Tensor([0.9743833], shape=(1,), dtype=float32)
Cc1oncc1C(=O)Nc2ccc(cc2)C(F)(F)F tf.Tensor([0.20397694], shape=(1,), dtype=float32)
CN(CCOc1ccc(CC2SC(=O)NC2=O)cc1)c3ccccn3 tf.Tensor([0.00319248], shape=(1,), dtype=float32)
OC(Cn1cncn1)(Cn2cncn2)c3ccc(F)cc3F tf.Tensor([0.0002369], shape=(1,), dtype=float32)
Cc1ccccc1OCC(O)CNCCOc1ccc(C(N)=O)cc1 tf.Tensor([0.07052732], shape=(1,), dtype=float32)
COc1c2OC(=O)C=Cc2cc3ccoc13 tf.Tensor([1.9813007e-05], shape=(1,), dtype=float32)
C(C1CN2CCC1CC2)N1C2=CC=CC=C2SC2=CC=CC=C12 tf.Tensor([0.99995106], shape=(1,), dtype=float32)
c1ccc2c(c1)N(c3cc(ccc3S2)Cl)CCCN4CCN(CC4)CCO tf.Tensor([0.9999804], shape=(1,), dtype=float32)
CC(C)(C)C1=CC=C(C=C1)C(O)CCCN1CCC(CC1)C(O)(C1=CC=CC=C1)C1=CC=CC=C1 tf.Tensor([0.5904768], shape=(1,), dtype=float32)
NC(=O)c1ncn(C2OC(CO)C(O)C2O)c1O tf.Tensor([0.00181772], shape=(1,), dtype=float32)
COc1cc2nc(nc(N)c2cc1OC)N3CCN(CC3)C(=O)C4COc5ccccc5O4 tf.Tensor([0.00666349], shape=(1,), dtype=float32)
ClCCN(CCCl)P1(=O)NCCCO1 tf.Tensor([1.0380586e-06], shape=(1,), dtype=float32)
CCN1C=CC(=NC1=O)NS(=O)(=O)c2ccc(N)cc2 tf.Tensor([1.3638827e-06], shape=(1,), dtype=float32)
CCCCC1C(=O)N(N(C1=O)c2ccc(O)cc2)c3ccccc3 tf.Tensor([0.15426806], shape=(1,), dtype=float32)
Cc1cccc(c1)N2CC(OC2=O)CO tf.Tensor([0.49775884], shape=(1,), dtype=float32)
c1ccnc(c1)C2=NCC(=O)Nc3c2cc(cc3)Br tf.Tensor([0.9838277], shape=(1,), dtype=float32)
CC(CN(C)C)C(C)(O)Cc1ccc(Cl)cc1 tf.Tensor([0.99803215], shape=(1,), dtype=float32)
CC(C)NCC(COc1ccccc1OCC=C)O tf.Tensor([0.0225733], shape=(1,), dtype=float32)
CN(C)C\C=C(\C1=CC=C(Br)C=C1)C1=CC=CN=C1 tf.Tensor([0.99852556], shape=(1,), dtype=float32)
CCCCNc1ccc(cc1)C(=O)OCCOCCOCCOCCOCCOCCOCCOCCOCCOC tf.Tensor([0.9999202], shape=(1,), dtype=float32)
CN(C)C(=O)Oc1ccc[n+](C)c1 tf.Tensor([4.904385e-07], shape=(1,), dtype=float32)
CCC1(CCC(=O)NC1=O)c2ccc(N)cc2 tf.Tensor([0.29386994], shape=(1,), dtype=float32)
Nc1ccc(C(=O)Oc2ccccc2)c(O)c1 tf.Tensor([0.00081717], shape=(1,), dtype=float32)
CNCCCC12CCC(c3c1cccc3)c4c2cccc4 tf.Tensor([0.94158566], shape=(1,), dtype=float32)
CN1CC(=O)N2C(Cc3c([nH]c4ccccc34)C2c5ccc6OCOc6c5)C1=O tf.Tensor([0.83776134], shape=(1,), dtype=float32)
CCC1(CC(=O)NC1=O)C tf.Tensor([0.04184898], shape=(1,), dtype=float32)
CC(C)(C)C(=O)OCOP(=O)(COCCn1cnc2c(N)ncnc12)OCOC(=O)C(C)(C)C tf.Tensor([3.6779713e-07], shape=(1,), dtype=float32)
COC1=CC=C2C(=CC1=O)C(CCc3cc(OC)c(OC)c(OC)c23)NC(=O)C tf.Tensor([0.24981706], shape=(1,), dtype=float32)
CC(CN1c2ccccc2Sc3c1cc(cc3)OC)CN(C)C tf.Tensor([0.9991838], shape=(1,), dtype=float32)
[H][C@]12SCC(C)=C(N1C(=O)[C@H]2NC(=O)[C@H](N)C1=CC=CC=C1)C(O)=O tf.Tensor([1.0444633e-05], shape=(1,), dtype=float32)
Cc1onc(NS(=O)(=O)c2ccc(N)cc2)c1 tf.Tensor([1.1462779e-08], shape=(1,), dtype=float32)
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深度网络 矩阵行列式
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