BMS Model Evaluation.ipynb

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    "tags": []
   },
   "source": [
    "# Imports"
   ]
  },
  {
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   "execution_count": 1,
   "id": "radical-novel",
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   "source": [
    "!pip install -q efficientnet\n",
    "import efficientnet.tfkeras as efn\n",
    "\n",
    "import os, pickle\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "from math import log\n",
    "from numpy import array\n",
    "from numpy import argmax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "going-democrat",
   "metadata": {
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   "outputs": [],
   "source": [
    "# seed everything\n",
    "SEED = 4546\n",
    "os.environ['PYTHONHASHSEED'] = str(SEED)\n",
    "np.random.seed(SEED)\n",
    "tf.random.set_seed(SEED)\n",
    "TPU= False\n",
    "\n",
    "# image resolution\n",
    "IMG_HEIGHT = 256\n",
    "IMG_WIDTH = 448\n",
    "N_CHANNELS = 3\n",
    "# maximum InChI length is 200 to prevent too much padding\n",
    "MAX_INCHI_LEN = 200\n",
    "\n",
    "BATCH_SIZE= 30\n",
    "# ImageNet mean and std to normalize training images accordingly\n",
    "IMAGENET_MEAN = tf.constant([0.485, 0.456, 0.406], dtype=tf.float32)\n",
    "IMAGENET_STD = tf.constant([0.229, 0.224, 0.225], dtype=tf.float32)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "grave-education",
   "metadata": {
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    },
    "tags": []
   },
   "source": [
    "# Data Pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "sized-synthetic",
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    "tags": []
   },
   "outputs": [],
   "source": [
    "# dictionary to translate a character to the integer encoding\n",
    "with open('../input/bmstfrecord-data/vocabulary_to_int.pkl', 'rb') as p:\n",
    "    vocabulary_to_int= pickle.load(p)\n",
    "    \n",
    "# dictionary to decode an integer encoded character back to the character\n",
    "with open('../input/bmstfrecord-data/int_to_vocabulary.pkl', 'rb') as p:\n",
    "    int_to_vocabulary= pickle.load(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "color-stuart",
   "metadata": {
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   "source": [
    "START_TOKEN = tf.constant(vocabulary_to_int.get('<start>'), dtype=tf.int64)\n",
    "END_TOKEN = tf.constant(vocabulary_to_int.get('<end>'), dtype=tf.int64)\n",
    "PAD_TOKEN = tf.constant(vocabulary_to_int.get('<pad>'), dtype=tf.int64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "banned-mentor",
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   "outputs": [],
   "source": [
    "def decode_tfrecord(record_bytes):\n",
    "    feature= tf.io.parse_single_example(record_bytes,{\n",
    "        'image': tf.io.FixedLenFeature([], tf.string),\n",
    "        'InChI': tf.io.FixedLenFeature([MAX_INCHI_LEN], tf.int64)\n",
    "    })\n",
    "    # decode the PNG and explicitly reshape to image size (required on TPU)\n",
    "    image = tf.io.decode_png(feature['image'])    \n",
    "    image = tf.reshape(image, [IMG_HEIGHT, IMG_WIDTH, 1])\n",
    "    # normalize according to ImageNet mean and std\n",
    "    image = tf.cast(image, tf.float32)  / 255.0\n",
    "    image = (image - IMAGENET_MEAN) / IMAGENET_STD\n",
    "    \n",
    "    if TPU: # if running on TPU image needs to be cast to bfloat16\n",
    "        image = tf.cast(image, TARGET_DTYPE)\n",
    "    \n",
    "    InChI = tf.reshape(feature['InChI'], [MAX_INCHI_LEN])\n",
    "    InChI = tf.cast(InChI, tf.uint8)\n",
    "    #InChI= tf.one_hot(InChI, depth= 41)\n",
    "    \n",
    "    return image, InChI\n",
    "\n",
    "def get_val_dataset(bs=BATCH_SIZE):\n",
    "    FNAMES_TRAIN_TFRECORDS = tf.io.gfile.glob('../input/bmstfrecord-data/val/*.tfrecords')\n",
    "    AUTO= tf.data.experimental.AUTOTUNE\n",
    "    val_dataset = tf.data.TFRecordDataset(FNAMES_TRAIN_TFRECORDS, num_parallel_reads=AUTO)\n",
    "    val_dataset = val_dataset.prefetch(AUTO)\n",
    "    val_dataset = val_dataset.repeat()\n",
    "    val_dataset = val_dataset.map(decode_tfrecord, num_parallel_calls=AUTO)\n",
    "    val_dataset = val_dataset.batch(BATCH_SIZE, drop_remainder=True)\n",
    "    val_dataset = val_dataset.prefetch(1)\n",
    "    \n",
    "    return val_dataset\n",
    "\n",
    "val_dataset = get_val_dataset()"
   ]
  },
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   "execution_count": 6,
   "id": "tested-rehabilitation",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "imgs.shape: (30, 256, 448, 3), lbls.shape: (30, 200)\n"
     ]
    }
   ],
   "source": [
    "imgs, lbls = next(iter(val_dataset))\n",
    "print(f'imgs.shape: {imgs.shape}, lbls.shape: {lbls.shape}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "induced-teaching",
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     "status": "completed"
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    "tags": []
   },
   "source": [
    "# Model Config."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "looking-challenge",
   "metadata": {
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   "outputs": [],
   "source": [
    "VOCAB_SIZE= 41\n",
    "DECODER_DIM = 512\n",
    "ATTENTION_UNITS = 256"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "academic-letter",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "class Encoderv1(tf.keras.Model):\n",
    "    \"\"\"Encoderv1\"\"\"\n",
    "    def __init__(self):\n",
    "        super(Encoderv1, self).__init__()\n",
    "        #output (8, 14, 1408)\n",
    "        self.fea_ext = efn.EfficientNetB2(include_top=False, weights='noisy-student')\n",
    "        global ENCODER_DIM\n",
    "        ENCODER_DIM = self.fea_ext.layers[-1].output_shape[-1] \n",
    "        self.reshape = tf.keras.layers.Reshape([-1, ENCODER_DIM], name='reshape_featuere_maps')\n",
    "        self.permuate = tf.keras.layers.Permute([2, 1], name='permutate_features_last')\n",
    "    def call(self, x, training):\n",
    "        x = self.fea_ext(x, training=training)\n",
    "        x = self.reshape(x, training=training)\n",
    "        x = self.permuate(x, training=training)\n",
    "        return x\n",
    "\n",
    "class BahdanauAttention(tf.keras.layers.Layer):\n",
    "    \"\"\"BahdanauAttention\"\"\"\n",
    "    def __init__(self, units):\n",
    "        super(BahdanauAttention, self).__init__()\n",
    "        self.W1= tf.keras.layers.Dense(units, name='hidden_to_attention_units')\n",
    "        self.W2= tf.keras.layers.Dense(units, name='encoder_to_attention_units')\n",
    "        self.V= tf.keras.layers.Dense(1, name='score_to_alpha')\n",
    "    def call(self, h, encoder_res, training):\n",
    "        # dense hidden state to attention units size and expand dimension\n",
    "        hidden_with_time_axis = tf.expand_dims(h, 1)\n",
    "        hidden_with_time_axis = self.W1(hidden_with_time_axis, training=training)\n",
    "        # dense features to units size\n",
    "        encoder_res_dense = self.W2(encoder_res, training=training)\n",
    "        # add vectors\n",
    "        score = tf.math.tanh(hidden_with_time_axis + encoder_res_dense)\n",
    "        score = self.V(score, training=training)\n",
    "        # create alpha vector size (bs, layers)        \n",
    "        attention_weights = tf.nn.softmax(score, axis=1)\n",
    "        # create attention weights (bs, layers)\n",
    "        context_vector = encoder_res * attention_weights #  tf.expand_dims(attention_weights, axis=2)\n",
    "        context_vector = tf.reduce_sum(context_vector  , axis=2)\n",
    "        return context_vector, attention_weights\n",
    "\n",
    "class Decoder(tf.keras.Model):\n",
    "    def __init__(self, vocab_size, attention_units, encoder_dim, decoder_dim):\n",
    "        super(Decoder, self).__init__()\n",
    "        self.vocab_size = vocab_size\n",
    "        self.attention_units = attention_units\n",
    "        self.encoder_dim = encoder_dim\n",
    "        self.decoder_dim = decoder_dim\n",
    "        # LSTM hidden and carry state initialization\n",
    "        self.init_h = tf.keras.layers.Dense(units=decoder_dim, input_shape=[encoder_dim], name='encoder_res_to_hidden_init')\n",
    "        self.init_c = tf.keras.layers.Dense(units=decoder_dim, input_shape=[encoder_dim], name='encoder_res_to_inp_act_init')\n",
    "        # The LSTM cell\n",
    "        self.lstm_cell = tf.keras.layers.LSTMCell(decoder_dim, name='lstm_char_predictor')\n",
    "        # dropout before prediction\n",
    "        self.drop = tf.keras.layers.Dropout(0.3, name='prediction_dropout')\n",
    "        # fully connected prediction layer\n",
    "        self.fcn = tf.keras.layers.Dense(units=vocab_size, input_shape=[decoder_dim], activation='softmax', dtype=tf.float32, name='lstm_output_to_char_probs')\n",
    "        # character embedding layer\n",
    "        self.embedding = tf.keras.layers.Embedding(vocab_size, decoder_dim)\n",
    "\n",
    "        # used for attention\n",
    "        self.attention = BahdanauAttention(self.attention_units)\n",
    "    def call(self, char, h, c, enc_output, training):\n",
    "        \n",
    "        # embed previous character\n",
    "        char = self.embedding(char, training=training)\n",
    "        char = tf.squeeze(char, axis=1)\n",
    "        #print('------', char.shape)\n",
    "        # get attention alpha and context vector\n",
    "        context, _ = self.attention(h, enc_output, training=training)\n",
    "\n",
    "        # concat context and char to create lstm input\n",
    "        lstm_input = tf.concat((context, char), axis=-1)\n",
    "        \n",
    "        # LSTM call, get new h, c\n",
    "        _, (h_new, c_new) = self.lstm_cell(lstm_input, (h, c), training=training)\n",
    "        \n",
    "        # compute predictions with dropout\n",
    "        output = self.drop(h_new, training=training)\n",
    "        output = self.fcn(output, training=training)\n",
    "\n",
    "        return output, h_new, c_new\n",
    "    def init_hidden_state(self, encoder_out, training):\n",
    "        mean_encoder_out = tf.math.reduce_mean(encoder_out, axis=1)\n",
    "        h = self.init_h(mean_encoder_out, training=training)  # (batch_size, decoder_dim)\n",
    "        c = self.init_c(mean_encoder_out, training=training)\n",
    "        return h, c"
   ]
  },
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   "cell_type": "code",
   "execution_count": 9,
   "id": "precise-fourth",
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     "status": "completed"
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    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://github.com/qubvel/efficientnet/releases/download/v0.0.1/efficientnet-b2_noisy-student_notop.h5\n",
      "31784960/31782304 [==============================] - 1s 0us/step\n"
     ]
    }
   ],
   "source": [
    "encoder = Encoderv1()\n",
    "encoder_res = encoder(imgs)\n",
    "decoder = Decoder(VOCAB_SIZE, ATTENTION_UNITS, ENCODER_DIM, DECODER_DIM)\n",
    "h, c = decoder.init_hidden_state(encoder_res, training=False)\n",
    "preds, h, c = decoder(tf.random.uniform((BATCH_SIZE, 1)), h, c, encoder_res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "useful-tyler",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-05T14:17:37.116947Z",
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     "start_time": "2021-05-05T14:17:37.003102",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "encoder.load_weights('../input/colabmodels-bms/BMS Model/encoder-imgnet-colab.h5')\n",
    "decoder.load_weights('../input/colabmodels-bms/BMS Model/decoder-imgnet-colab.h5')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "level-dominican",
   "metadata": {
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     "duration": 0.023038,
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     "start_time": "2021-05-05T14:17:38.941265",
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    "tags": []
   },
   "source": [
    "# Model Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "comprehensive-haiti",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_pred(imgs):\n",
    "    enc_output = encoder(imgs, training=True)\n",
    "    h, c = decoder.init_hidden_state(enc_output, training=True)\n",
    "    dec_input = tf.zeros((imgs.shape[0], 1), tf.uint8)\n",
    "    predictions_seq = dec_input\n",
    "    for t in range(1, MAX_INCHI_LEN):\n",
    "        predictions, h, c = decoder(dec_input, h, c, enc_output, training=False)\n",
    "        dec_input= tf.expand_dims(tf.argmax(predictions, 1), 1)\n",
    "        dec_input= tf.cast(dec_input, tf.uint8)\n",
    "        predictions_seq=  tf.concat([predictions_seq, dec_input], axis=1)\n",
    "        if t==1:\n",
    "            predictions_prob= predictions\n",
    "        else:\n",
    "            predictions_prob= tf.concat([predictions_prob, predictions], axis=1)\n",
    "    predictions_prob= tf.reshape(predictions_prob, (predictions_prob.shape[0], (MAX_INCHI_LEN-1), VOCAB_SIZE))\n",
    "    return predictions_seq, predictions_prob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "greenhouse-reform",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-05T14:17:39.076717Z",
     "iopub.status.busy": "2021-05-05T14:17:39.076053Z",
     "iopub.status.idle": "2021-05-05T14:17:39.078750Z",
     "shell.execute_reply": "2021-05-05T14:17:39.079252Z"
    },
    "papermill": {
     "duration": 0.033449,
     "end_time": "2021-05-05T14:17:39.079407",
     "exception": false,
     "start_time": "2021-05-05T14:17:39.045958",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def convert(inp):\n",
    "    string=''\n",
    "    for i in inp[1:]:\n",
    "        if i== 1:\n",
    "            break\n",
    "        string+= int_to_vocabulary[i]\n",
    "    return string\n",
    "\n",
    "def process_pred(pred):\n",
    "    str_list=[]\n",
    "    for i in range(pred.shape[0]):\n",
    "        str_list.append(convert(pred[i].numpy()))\n",
    "    return str_list "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "genetic-situation",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-05T14:17:39.141553Z",
     "iopub.status.busy": "2021-05-05T14:17:39.140911Z",
     "iopub.status.idle": "2021-05-05T14:17:39.144243Z",
     "shell.execute_reply": "2021-05-05T14:17:39.143704Z"
    },
    "papermill": {
     "duration": 0.041434,
     "end_time": "2021-05-05T14:17:39.144380",
     "exception": false,
     "start_time": "2021-05-05T14:17:39.102946",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def show(img, label, pred, bs_seq):\n",
    "    print('LABEL--',label)\n",
    "    print('\\n')\n",
    "    print('PREDICTED--',pred)\n",
    "    print('\\n')\n",
    "    print('BEAM SEARCH--',bs_seq)\n",
    "    plt.figure(figsize=(8, 8))\n",
    "    plt.imshow(-imgs[0])\n",
    "    plt.yticks([]);plt.xticks([])\n",
    "    plt.show()\n",
    "    \n",
    "# beam search\n",
    "def beam_search_decoder(data, k):\n",
    "    sequences = [[list(), 0.0]]\n",
    "    # walk over each step in sequence\n",
    "    for row in data:\n",
    "        all_candidates = list()\n",
    "        # expand each current candidate\n",
    "        for i in range(len(sequences)):\n",
    "            seq, score = sequences[i]\n",
    "            for j in range(len(row)):\n",
    "                candidate = [seq + [j], score - log(row[j])]\n",
    "                all_candidates.append(candidate)\n",
    "        # order all candidates by score\n",
    "        ordered = sorted(all_candidates, key=lambda tup:tup[1])\n",
    "        # select k best\n",
    "        sequences = ordered[:k]\n",
    "    return sequences\n",
    "\n",
    "def dense_to_sparse(dense):\n",
    "    ones = tf.ones(dense.shape)\n",
    "    indices = tf.where(ones)\n",
    "    values = tf.gather_nd(dense, indices)\n",
    "    sparse = tf.SparseTensor(indices, values, dense.shape)\n",
    "    \n",
    "    return sparse\n",
    "\n",
    "def get_levenshtein_distance(preds, lbls):\n",
    "    preds = tf.cast(preds, tf.int64)\n",
    "\n",
    "    preds = tf.where(tf.not_equal(preds, START_TOKEN) & tf.not_equal(preds, END_TOKEN) & tf.not_equal(preds, PAD_TOKEN), preds, y=0)\n",
    "    lbls = tf.cast(lbls, tf.int64)\n",
    "    lbls = tf.where(tf.not_equal(lbls, START_TOKEN) & tf.not_equal(lbls, END_TOKEN) & tf.not_equal(lbls, PAD_TOKEN), lbls, y=0)\n",
    "    \n",
    "    preds_sparse = dense_to_sparse(preds)\n",
    "    lbls_sparse = dense_to_sparse(lbls)\n",
    "\n",
    "    batch_distance = tf.edit_distance(preds_sparse, lbls_sparse, normalize=False)\n",
    "    mean_distance = tf.math.reduce_mean(batch_distance)\n",
    "    \n",
    "    return mean_distance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "finite-slovak",
   "metadata": {
    "papermill": {
     "duration": 0.023551,
     "end_time": "2021-05-05T14:17:39.191561",
     "exception": false,
     "start_time": "2021-05-05T14:17:39.168010",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Final Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "wired-essence",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-05T14:17:39.247184Z",
     "iopub.status.busy": "2021-05-05T14:17:39.245997Z",
     "iopub.status.idle": "2021-05-05T14:18:07.857790Z",
     "shell.execute_reply": "2021-05-05T14:18:07.857239Z"
    },
    "papermill": {
     "duration": 28.642627,
     "end_time": "2021-05-05T14:18:07.857942",
     "exception": false,
     "start_time": "2021-05-05T14:17:39.215315",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(TensorShape([30, 200]), TensorShape([30, 199, 41]))"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions_seq, predictions_prob= get_pred(imgs)\n",
    "predictions_seq.shape, predictions_prob.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "cultural-excuse",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-05T14:18:07.917659Z",
     "iopub.status.busy": "2021-05-05T14:18:07.916595Z",
     "iopub.status.idle": "2021-05-05T14:21:55.769840Z",
     "shell.execute_reply": "2021-05-05T14:21:55.769225Z"
    },
    "papermill": {
     "duration": 227.887596,
     "end_time": "2021-05-05T14:21:55.769994",
     "exception": false,
     "start_time": "2021-05-05T14:18:07.882398",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LABEL-- C31H27ClN2O7S/c1-6-40-30(37)26-17(3)33-31-34(27(26)22-14-19(32)8-11-23(22)38-4)28(35)25(42-31)15-20-9-12-24(41-20)21-10-7-18(13-16(21)2)29(36)39-5/h7-15,27H,6H2,1-5H3/b25-15-/t27-/m0/s1\n",
      "\n",
      "\n",
      "PREDICTED-- C31H27ClN2O7S/c1-6-40-29(36)26-17(3)33-31-34(27(26)24-14-19(32)9-12-23(22)38-5)28(35)24(42-31)15-20-1-11-22(41-20)20-10-7-17(13-1((2))2)29(36)40-4/h7-15,27H,6H2,1-5H3/b26-15-/t27-/m0/s1\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 31H27ClN2O7S/c1-6-40-29(36)26-17(3)33-31-34(27(26)24-14-19(32)9-12-23(22)38-5)29(35)24(42-31)15-20-1-11-22(41-20)20-10-7-17(13-1((2))2)29(36)40-4/h7-15,27H,6H2,1-5H3/b26-15-/t27-/m0/s1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 19.0\n",
      "LD for BEAM SEARCH- 20.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C26H25N3O2S2/c1-31-21-11-4-3-9-19(21)27-26(30)29-16-18-17-8-2-5-12-22(17)33-25(18)28-14-6-10-20(28)24(29)23-13-7-15-32-23/h3-4,6-7,9-11,13-15,24H,2,5,8,12,16H2,1H3,(H,27,30)\n",
      "\n",
      "\n",
      "PREDICTED-- C26H25N3O2S2/c1-31-20-11-4-2-9-18(21)27-26(30)29-16-19-17-8-2-5-12-22(17)33-25(22)28-14-1-11-11-22-22-22-2--1-13-13-23-22/h2-4,7,8-11,14,15,2,H,,,,,,,11,1,HH,1H,,,,,2,,3<pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad>\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 26H25N3O2S2/c1-31-20-11-4-2-9-18(21)27-26(30)29-16-19-17-8-2-5-12-22(17)33-25(22)28-14-1-11-1--22-22-22-2--1-13-13-23-22/h2-4,7,8-11,14,15,2,H,,,,,,,11,1,HH,1H,,,,,2,,3<pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad>\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 46.0\n",
      "LD for BEAM SEARCH- 46.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C23H30N2O4S/c1-3-29-21-13-15-22(16-14-21)30(27,28)25(20-11-9-18(2)10-12-20)17-23(26)24-19-7-5-4-6-8-19/h9-16,19H,3-8,17H2,1-2H3,(H,24,26)\n",
      "\n",
      "\n",
      "PREDICTED-- C23H30N2O4S/c1-3-29-21-13-15-22(16-14-21)30(27,28)25(20-11-9-18(2)10-12-20)17-23(26)24-19-7-5-4-6-8-19/h9-16,19H,3-8,17H2,1-2H3,(H,24,26)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 23H30N2O4S/c1-3-29-21-13-15-22(16-14-21)30(27,28)25(21-11-9-18(2)10-12-20)17-23(26)24-19-7-5-4-6-8-19/h9-16,19H,3-8,17H2,1-2H3,(H,24,26)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C20H20ClN3O4/c1-11-16(19(25)23-14-9-5-4-8-13(14)21)17(24-20(26)22-11)12-7-6-10-15(27-2)18(12)28-3/h4-10,17H,1-3H3,(H,23,25)(H2,22,24,26)\n",
      "\n",
      "\n",
      "PREDICTED-- C20H20ClN3O4/c1-11-15(19(25)23-14-9-5-4-8-13(14)21)17(24-20(26)22-11)12-7-6-10-15(27-2)18(12)28-3/h4-10,17H,1-3H3,(H,23,25)(H2,22,24,26)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 20H20ClN3O4/c1-11-15(19(25)23-14-9-5-4-8-13(14)21)17(24-20(26)23-11)12-7-6-10-15(27-2)18(12)28-3/h4-10,17H,1-3H3,(H,23,25)(H2,22,24,26)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 1.0\n",
      "LD for BEAM SEARCH- 2.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C16H14F3NO3/c1-22-15(21)10-6-7-12(17)13(8-10)20-9-11-4-2-3-5-14(11)23-16(18)19/h2-8,16,20H,9H2,1H3\n",
      "\n",
      "\n",
      "PREDICTED-- C16H14F3NO3/c1-22-15(21)10-6-7-12(17)13(8-10)20-9-11-4-2-3-5-14(11)23-16(18)19/h2-8,16,20H,9H2,1H3\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 16H14F3NO3/c1-22-15(21)11-6-7-12(17)13(8-10)20-9-11-4-2-3-5-14(11)23-16(18)19/h2-8,16,20H,9H2,1H3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C11H9IN2/c12-11-10(13-6-7-14-11)8-9-4-2-1-3-5-9/h1-7H,8H2\n",
      "\n",
      "\n",
      "PREDICTED-- C11H9IN2/c12-11-10(13-6-7-14-11)8-9-4-2-1-3-5-9/h1-7H,8H2\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 11H9IN2/c12-11-10(13-7-7-14-11)8-9-4-2-1-3-5-9/h1-7H,8H2\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C11H12BrN7O/c1-7(8-2-4-9(12)5-3-8)14-15-10(20)6-19-17-11(13)16-18-19/h2-5,14H,1,6H2,(H2,13,17)(H,15,20)\n",
      "\n",
      "\n",
      "PREDICTED-- C11H14BrN7O/c1-7(8-2-4-9(12)5-3-8)14-15-10(20)6-19-17-11(13)16-18-19/h2-5,7,14H,6H2,1H3,(H2,13,19)(H,15,20)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 11H14BrN7O/c1-7(8-2-4-9(12)5-3-8)14-15-10(20)6-19-17-11(13)16-18-19/h2-5,7,14H,6H2,1H3,(H2,13,18)(H,15,20)\n"
     ]
    },
    {
     "data": {
      "image/png": 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3OXjwILfyIyKXM2SACiFaDc+7d+9CCOG0Lz8/P4vH9Pf3R21tLd+oDUjbyo+IyFUMF6CNjY1tOhuLtkuRs75sDV/U1tYiMDCQIUpEHqmurs7qWlAA6N69OzdTMGOoAG1reKrGECUiT2ZrQwWuA23KUAEK3Bu+NfLpzPz9/VFdXa2HKBGRp7E2ichTw7MjjZBhAtRduk/g3obL1dXVADj7k4i8h6e835kfrhNC2P1zGSJAtfA0evdpLiAgAFevXkVQUJDHvKiIiFriCcdAtdDUvkwmk92b4ygPUJPJ5Hbhaa6mpgZBQUGqyyAicig/Pz+PHMbV9lY3mUyQUnZoZznlAQoY/7inLQEBAaiqqlJdBhGRS7hzB2q+vr8jXac59zjoaGCBgYGorq7u8CcZIiJyDm3YFnBceAIG6EB9fHzcsvs0V11djeDgYB4LJSKPUFdX12TzeHffnc0Z4QkoDlCTyQRfX1+VJTiMFqJERJ5COw7q5+cHIQR++OEH1SW1mXnoa//v6FFCZQHqSeEZGBiIyspKAJ4zzZuIvJO1brO+vl6/PDQ0FN9//72hu1LzmbbOrFFJgGrh6ePjA5PJpKIEp6iurtZP0k1E5G6klPD394cQArdv37a6rd/333+P0NBQPaCM1pU663inNco6UE8Lz6CgIFRWVqKqqgohISGqyyEiajOtmwwICEB9fb1+0gxbe+JqHej999+Pbt266SGqqnkw74Z9fX0dskSlLVweoNq6T08KT01QUBAqKipUl0FELmTkocy2kFIiMDAQQggUFRVBSmn1bFTW/PDDD5BSomvXrgCArl274s6dOy59TqSU8PX11TdFcHbXaU75LFxPExwcjMrKSrf+gyKitpFSYsCAARBC4OLFi6rLaTctPGtra1FdXQ1/f/8O3d8//vEP3Hfffbj//vshhNDD1Fm08GxoaGgydOsqLg9QTxu6taayspLDuEQeTkqJgQMH6sH50EMP4eLFi27z4bl5eAYEBDjsvu/cuYOf/exnepD+85//dMrz4uvrq/T5dmmAetLM27Zw96EdImrKfBPygQMH4qOPPmpy2YwZMyCEwOXLl/XbG41Wa1BQEK5evaof+3Q0rfvs0qUL7rvvPggh8K9//avV90Vr52e2RTvW6erOU+OyR/XkY5/NBQcHIzc3F0II9OzZU3U5ROQggwcP1meffvTRRxgwYECT67UOtH///gCA/v37Izc31xAfprUagoODIYRAQUGBU4KzOa371ML0Zz/7mR6m1mrs3Llzk83ejbzVq0sCVBun9ibBwcG4desWAGN+CiWi9tH+jnNycvRjn63Jzc3F1KlT9SDIz893dpk2hYSE6DVow7cqaF1oly5dLK7r0qULGhsbcffuXT10fX190alTJ0OGqMs6UG849mlNZWUlQkNDVZdBRHbSgnPIkCFITU1FYmJiu75f60Dj4uIQHx+PgoKCJvfrbObdb0VFhWHPHqXVePfu3Sbnhm5oaIAQwpAh6vQA1canvTE8Q0JC2IUSubmhQ4ciJycHOTk5NsOzLUO0Wuf385//HAUFBYiNjUVhYaEzSm5Sl9Z55ubmGnq70S5duqChocHqdY2NjcqOc7ZEaUVGOC7gChUVFYbpQj3xOX/yySdx4MABAPygQo7R3teR+VKW1ia/aOEJALGxsfpEHkf+bWr307NnT1RVVaGiosLQ4dkWDQ0NhjsU6LIAbf7CMJlMEEIY7gnxRAkJCbh06RIuXboEIQQeeughjwgaKSUOHjwIIQRmzpyJTz75BLNmzfKIn43UGj58OM6ePQsAOHfuHAYPHtzi7S9cuAApJR588EE8+OCD+jHP3Nxcm99TWFgIKSWio6MRHR2tf4+2mYG9tP1qKyoqUFFRoU8ccndeOYSraR6URp5Z5WjmQ7mulpubiwceeABSSjzwwAO4cOECLl26hAEDBrh10Hz22Wd46qmnANzrQKWUOHDgAD7++GOGKNnFUV3gpUuXIKVEQkKCPgtXu39brl27pj/2mDFjIIRAcXGxXfX36tXLI3dEM2IHanXNja2vpKQkaQ+TySR9fHykyWRqcnljY6P08fGx6z7dwa1btyQAGRISoqyGy5cvSwCyf//++mUXLlyQAORDDz0kTSaTxe/F6P70pz9JAHLatGkW1+3fv18CkLNmzVJQGbkrk8kkk5KSJAAJQJ45c8Yh9xsfHy8ByNzcXBkXFyfz8vLa9H0RERESgCwuLm7z32doaKhe/82bNztSthKdOnWSAOTdu3ctrjOZTFIIIRsaGlxe14+5ZzUTXTqE23zXCE+ZXCStfLLULjNfzqJCQkICTCYTLl26pF/24IMP4rvvvsOFCxcghEBiYqLhj41q9R06dAjTpk3D1KlT8emnn1rcbubMmdi/f7/F9xFZo70+Ro4ciezsbJw+fVprFhxy/9oM3Pj4eADQZ+GavwlbU1xcDCklRo0aBSEESkpKrH5P83/fuHEDUkq3XH+uzb7t3LmzvjWf9mXYPQRsJau1L3s7UCnvdZsAbHac7tYFaaqqqmRAQECTyyoqKiQAGRwcrKiqn1y+fFkmJCS0eJvz589LAHLQoEGG7EgPHTokAchf/OIX7fq+ffv2SQBy9uzZhvuZSD2TySRHjBghAcisrCyXPnZMTIzeLRYWFrbp9RkWFqZ/T0lJiZRSyl69ekkAsry83Nklu5yvr6/+86roPDUtdaCdrKaqE2jHPM3X92gaGxv1Kcyu2kXfEWpqahAUFGR1Nw+jnJklPj5e31bMlkGDBkFKifPnz+sd6blz55T/LqSU+OKLL7Bp0ya7usjZs2cDAObMmQMA2Ldvn0PrI/clpURycjJOnz6NrKwsjBgxwqWPr60FjYmJQUxMDADg6tWriIyMtPl3V1paqv9/eHg4srOzAQBlZWXo1auXkyt2PVtLWozEpctYtCFba2+G2lZ/7iYgIADV1dWqy7AqNzdX31KsLRITE5GTk4Pz589j6NChyoY/teAUQuCJJ57oUJDPnj0bH374IXx8fDiUSwB+Cs9vvvkG33zzjcvD05w2EzcyMhIAEBUVhaKiola/r7S0FMOGDcO5c+fQu3dvZ5dJNig5H2jzY6Ha6WjcSU1Njc2tsLSTa6uWkJDQavfZnNZ95uTkQAiBYcOGuTRIjxw5gkmTJgEAJk2aBCkl/vznP3foPufMmYPp06fjmWee4TFRL6b93kePHo23335bP/ZpBNeuXUNUVBSAeyGqHQPla9XYlGykIKXl3ri+vr76shajv2hqamoQHR0NKaVF92mkU5m1twPVDB48WP/j3bFjB4QQGD58uNP+oM2PKTz++OM4cuQIJk+ejC+++MJhjzFnzhxMmzYNQgjMnTvX8K8xciwpJVJSUpCZmYnMzEyMGjVKdUlWaWtA+/bti8jISH0CERmTywPUfP2ntTcxW8dJjaK2ttZm51lVVWWY8ATadvyzNdpQ7tatWyGEwIgRIxwapMeOHdMXkD/++OMOuU9bnn76abz//vv44IMPMH/+fIaol9DCc/369UhOTlZdTptpXWifPn1Ul0I2KNvKT+tC3fFNzN/fHzU1NU0uq6qqQnBwsGGGb/Py8iCEsKsDtSYpKQlnzpxBdnY2hBA2h77a8/s8duwYJk6ciIkTJ0JKiS+//NIhtbbk6aefhpQSkydPZoh6OO2D3pgxY7B+/XqMHj1adUkOFxYWhvLyctVleC0lAap1oS0N5brjG1tgYKAhwlN77uLj41vcSqy9kpKSIKVEVlaW1eszMzORkpJi8btr6Xf56KOP4quvvnJYjW01b948TJ48GQsWLHDL1xq1buzYsRBCYN26dR4ZnqSesg60pa38Ghsb0blzZ8O9sUkp4efnZ9F9VldXG2avyfz8fCQkJDg8PM2NGDECp0+ftnpd8xA9efIkxo4da/V3OWHCBBw7dswpNbZVamoqQ9SDpaWlISUlRXUZ5KGUno2lpWUtRgvRuro6CCFsnsE9MDAQVVVVri3Kiri4OKcFZ1tlZmZizJgx+r/T09Mxbtw4hRVZN2/ePH3i0qJFiwzzWiNqC09d/+lOlJ9gzdr6T+3Y6J07d9C5c2dFlVny8/NDbW2txeUBAQGGCM/8/HwIIZCQkKAsDJKTk5GRkaHkse01f/58TJgwAYsWLVJdCrkAPyiRoygPUE1LL2rVL/i6ujr4+/tbva66utowZ3iPi4tDXl6ePoyrmurfW3ssXLgQu3btUl0GucDo0aNx6tQp1WWQBzBEgGpdaEtDuar16NHDovvUtvIzgoKCAsTHx6Nfv34wmUxKh3FHjx6NdevWNRnGdVfma1TNLyP3MHbsWLcbESH3oTxAhRCQUuJf//qXRYh26tQJd+/eVVjdPT169EBdXV2Ty7SdiIywlZ+UEjExMXr3qQ3jqpSSkuL2b1zbt2/X16guW7YMALBlyxasXLlScWVEZASG2rFA60TNZ+d26tRJP7WNis3N6+vr0adPH4sADQgIgMlkUr7hemFhIWJjY/V/x8XFGaIuAMjIyMDYsWNVl9Fhzz33HLZt2wYAWLFiheJqqK1OnjyJRx55RHUZ5MGUd6Aa8/1wmw+RNTQ0KJuR2717d4vwBFreC9eVYmJiYDKZcOXKFQDAlStXlHefnmTx4sXYunWr6jKIbAoLC8ONGzdUl+GVDBOgwL0Q1YZym1OxrKW+vh5+fn4Wl2t74TZfD6qC1oHGxsZCSom8vDzVJXmUHTt2YNmyZfrrjht8E5HGUAFqrvmxUG1ZS5cuXVzy+PX19QgPD0d9fX2Ty2traw0TnsC9DrSwsBDAvWUskydPVhaiycnJ+Prrr/V/axsqSCmRlpampKaOWLJkiX7GjmXLluHdd9+FEAIrV65kiLoxI28m317l5eVcC6qQ4QJU60JVz7zt0aOHRXgCsLoTkVH069cP+fn5qsvwOEuXLsW2bduwfPlySCkxZMgQrFq1SnVZRKSY4QLUXPNP+apn5dbW1trciYi8A2fhup8xY8Y0GRkhchTDBqhR1n8SNbd8+XJs2rRJdRlEpJghA9TX11fvNI0yaaOurs4Q3aet58Ioz1NzRq2rI959910O4bo5T3tNkhqGDFDg3nDtnTt3IITQZ9866gtAu25fV1eHiIgISCmt7oXrKkVFRYiOjra4vLCwEEIIxMfHu76oFmRkZEAI4RFrQTUrVqyAlBKbN29WXQq1wcmTJ62eyiw5OdmjtvPr3bs3l7IoYNgABX465tnY2KjvCNPRr65du+KHH35o1/fY2gfX1SIjI3H16lXVZbRZSkqKW86+Jc+Snp7O84GSUxg6QM2ZD+t2xJ07d9CtW7c237579+5Ku05ztjpQd8AhM1LF0ycRlZeXIzQ0VHUZXsnwAaqtAW1oaND/35Vf5ktZjBICRqmjrYx6PlAioo4wfIAagZ+fH65fv46AgADl4dW8C22+F67RPPLIIxzGJSKPZKjN5I1Om4mrakg3MjLSYqP4mJgYFBQUYOLEidzGz8FUncCAHCs9Pd3jf4/l5eUe/zMaETvQNjLCDkQtHQMtLCw03Czc5lR37+2xY8cOPPfcc6rLIAfw9GOgAGfhqsIAbQd/f3/U1tYaMgi084Ea1cmTJzF+/HjVZbTJjh07kJ6eju3bt6suhRwgIyPD5lKWrKwsBRWRp2CAtlNtba0hTmPWnJE70EceeQR//etfVZfRJjt37kR6ejp27NihuhQiC564MYk7Y4C6kcjISFy7ds3i8piYGEgpuZF8B+3atQvPPvus6jKIrJJSok+fPhBCoKysTHU5BE4iajd/f3/9WCgnmXiehQsXsvv0AqdOnXKrU5pp4VlWVobS0lKEhYU1uZ7HP9VgB2qnmpoaBAYGcjiFiJxKSomIiAiUlZWhpKTEIjxJHQZoB9TW1iIoKIghSmRw7vg3qh3vjIiIQGlpKUpKShAeHm71NqQGA9ROAQEBqK6uRk1NDYKCglSXY3hjx4419ESiXbt24dixY9i5c6fqUsgJUlJS3GYpixaKkZGREEIgKysLUsom4andJiwsDEIIDuEqwmOgHRAQEICqqipD7wRkNEY9brxgwQIsWLBAdRnkQkY9G0tUVBSKi4tRVFSEvn37Wr1NeHg4ysvLAQBlZWXo1auXK0ukH7ED7aDAwEBUV1erLsMt/PWvfzXkWtA9e/ZACIFFixapLoW8mNZVFhUVQUppMzy1D6GlpaWQUqJ3794urpQ0DFAH4bEI97ZgwQLs2rVLdRnkhbT3jujoaAghUFRU1OLt+/Tpg+zsbE4mMgAGqANUV1dDCIHg4GDVpbgFI33Q2LNnD44cOcLw9BJGeu0B9+qJiYmBEAJpaWn6sU9rt9NYW8ZCajBAHSAwMBCVlZUAjPcHajRpaWmYMGGC6jIAAKmpqTzu6eHMR4ZSUlIghEBmZqZh/k5jY2Nx4sQJSCkRFRVlcX3zmbhkLAxQB6qurkZISIjqMogI98Jn7NixEEJg/fr1kFLqmyckJyfj1KlTyoJUC8bCwkKbJ4jQjoNqM3GbL2Eh9RigDqKtB9U6UfqJlBJpaWlNJhA1P3G5KvPmzcOePXuUPT45nvZ6Gjt2LNLT05Genq5vJp+ZmYnk5GQA90JUCIHTp0+77HWoPUZcXByEECgsLLR528jISJSUlOD69evo06eP02uj9mOAklOdPHkSQgj87ne/g5QSJ06cwIkTJyCE0L8ee+wxi0A1f0Nz1hvb3LlzvTo8bT3f7kxKiXHjxiEtLQ0nT56ElBIpKSkWt9O6TyklRowYgZEjR0IIgTNnzuj34+i6pJSIj49HQUEBCgoK9OOfzW+nKS4u1rfwI2NigJLTjRkzBmlpaQCAcePG6W8mR48eBQAcPXq0SaBqX1OmTMHhw4fxi1/8okmYOiJgU1NTMX/+fI8IDXtIKbF69WqL5/zdd99VXZrdpJQYP348/uu//gtjx45t1/eePn0aSUlJGDFiBLKzszF8+HCcPXvWYXUlJCRACIErV660eLuoqKhWZ+GScTBAyWkyMjKwdu1anDx50uZtHn30Uaud0OHDh/GXv/wFTzzxBA4fPoypU6fi0KFDTd7sn3rqKRw8eBDTp0+32cG21Fnt3bvXaycRvfDCC9i8eTPeeecd/Tlavnw5VqxY4XYhqtU/fvx4/YOaPc6cOQMpJZKSkizuuyO19e/fH/n5+cjLy4OU0mLjFfNlLOnp6VZn4ZIxcSciFzHqDjyqHD9+HBMnTsSjjz5q9frJkydbfePSLvvss88wbdo0/OlPfwIACGH7s+CcOXPwwQcfAAB8fHzw/vvvY/78+U3u0xt/N++88w5WrVql/3vLli1u2ZFPnDgRx48fx4kTJzBu3DiH3Gd2djaGDh2Kc+fOAQDOnTuHwYMHt/t++vfvj7y8POTm5qJfv35WbxMTE4Nr167h6tWrDE83ww7UScw/ud66dQuhoaEWl3sqKSUyMjLw6quvWnSfUkocP34cEyZMwKOPPopjx47Z9Rj/9m//1mLH+dFHHwEAfvnLX2L69OkQQuCZZ57BBx98gLlz5+rHP7WlLJ7+OzHnCT9r87+jY8eOOSw8NWfPnoWUEoMHD8aQIUOQk5OjP7b5f1tz+fJli5PdN6//6tWrVpexkMG1NvRl/pWUlCSpdRUVFRKADA4ObnL5jRs3JAAZGhqqqDLny8jIkADk6NGjLa47ceKEBCDHjx/v8ro+/PBD+atf/crqdbt375YLFiyQJpPJxVWpsXr1arlhwwbVZdjFZDJJk8kkJ06cKAHIo0ePuryGQYMGyfPnz8uHHnpI/v3vf7frPmJiYiQAWVBQ4ODqyNF+zD2rmcgO1EmCgoJQUVHR5LLQ0FD9rAnSA7qA5jIzM5GSkoLk5GRkZGRYvc3YsWNx/PhxF1f2EymtjwDs3r2be+G6gccffxxCCBw9ehRffvmlkk05zp8/j0GDBuG7777D7NmzceHChTb/PWu3szULl9wLA9QJgoODLcLT3M2bNz12K67k5GSrp41KS0vDf/zHfyg7pdmcOXMwbdo0CCEwd+7cJtdps3G96VRmL7zwAjZt2mRxuZE/2Gm1HTlyBFJK/PznP1dc0T0DBgyAEAIXL15s8XbSbBkLeQYGqBNUVlZ63Y5Ep06dwpo1a6yGp1HelJ9++mlIKfH+++9b1LRr1y4sWrTIMLWqIKVscRau+dCVK2vSHm/SpEl49dVX8dhjj7ns8Vvz3Xff6TXOmDFDD9HmQ30AEB8f3+IyFnJDtsZ2rX3xGGjbVFRUyKCgIKvXacdBe/Xq5eKqnCczM1M+/PDDVq9LS0uTY8aMcXFFLdu7d6+cO3euxTHPnTt3yoULF3rFsdDVq1dLAPKdd96RUt47trh8+XK5ZcsWm9+zcOFCCUACkDt37tSPRzrT5MmTJQB5+PBhpz6OoyUkJOjPFQCZm5uruiSyE4+BktNkZWXhN7/5jdWTE7dlHagqe/fubbKURbNr1y4sWbJEQUWutXHjRjz//PP6v1euXIkhQ4Zg+fLlNr9n586d+hvHsWPH9PW4qampDu9KpVnndvjwYUyePNmh9+9sly9f1odsrc3CJQ9hK1mtfbEDbRutA7X26fzGjRseMwv3m2++kQBsdp/u2Mm999578tlnn3XL2lWYO3eu3mXt3bvXIV2pyWSSU6ZMkQDk559/7qBK1YiPj5eXL19WXQZ1ADtQBaqqqtCzZ08AP31IuXnzJnr16qW4Msc4ffo0Hn74YYwYMcKi+5Q/rgMdM2aMouraTlrpnN577z0sWbLEq4+HtpXWfT799NOYO3eu3pXu27fP6nHAlmi3mTp1Kg4fPozPP/8cU6ZMcfaPQGQ/W8lq7YsdaPvdunVL/4Tes2dP1eU4RFZWlhw+fLjV61paB2o0e/bskfPmzbPomLZv3y4ByMWLFyuqzDP88pe/bHIccP/+/S12p1OnTpWfffaZCyskal1LHSi38nOykJAQj+pkzpw5g5EjR2L48OEW17VlHajRpKamAkCTs7IsXrwYANzmZ2gLKV2/XaG2GxRwb0eoWbNmAQAOHDiA6dOnw8fHp0ldn332mUvrI+ooDuFSuwwfPhxSSpw+fdrq9bbWgRrRvHnzsHv3bgCWQ7mLFy/G9u3bPeLDj5QSL730EjZs2KCshj/+8Y/6Uo+ZM2dCCIGDBw/iqaeewqeffqqsLmeTbRy+JvfEACWHaGkdqNGlpqZaXQO6fft2PPfcc4qqcpw1a9bg//7v/1SXAeBe96mFys6dO/WTAXiq/v37QwiBvLw81aWQE3AI18FUDJWpdurUKSQnJ2PUqFGqS2k3bSmLdlqzXbt2WdzGnX+nUkq89dZbeOutt1SXQuRx2IE6UFVVldftQAQAo0aNgpQSmZmZqkuxy/z5861u47dkyRKMHj0ay5Ytc8thOCkl1qxZw/BUKDc3l2tAPRg7ULKqeWC4awfWVgsXLsTChQutdpt/+MMfAABbt251q+fh5ZdfRmRkJF566SXVpRB5JHagDlJVVYXg4GDVZThETk6Ovp5PCIFhw4apLskldu3ahWeffbbJZUuWLMHWrVvxhz/8AStWrFBUWfu5Y8dM5G4YoA5QXV2N4OBgBAYGorKyUnU5HXL+/Hn9BNNSSvztb3/Tr/OWN+XmMyeXLl2KrVu36tcZnZQSL7/8Mv73f/9XdSlEHo0B6iCBgYGoqqpSXUaHnD9/HoMHD25y2dChQ3H27FlkZ2dbXfvpSRYuXIjx48dDCGGxH+7SpUsxbNgwrFy5UlF1bSOlxCuvvILw8HB9+QoROQePgTpAQECA24enZtCgQcjJyVFdhjKLFi2CyWRCenq6282+1cKzd+/e+Pd//3fV5RB5PHagHVRdXY2goCDVZZCDvffeexZrQJcvX44tW7YYdhj3tddew5tvvqm6DLIiISEB+fn5qssgB2OAdoBR30g7ylN/rrbSdiGyZsuWLVi5cqXhniOtnv/5n//Byy+/rLgaIu/AALVTTU0NhBCIjY1FdXW16nIc5ttvv8WQIUNUl6Gcra38VqxYgSFDhmDVqlWKKrMkpcRvf/tbhISEMDwNKDc3F/369VNdBjkBA7QD/P39PSo8qanWtvIzQheqhee6detUl0LkdRigdqipqUFgYKDqMhwuMTFRn0Bkfsqes2fPYtmyZcjOzlZcoRrWutCBAwdi1apVykN07dq1WLduHd544w28+uqrSmsh8jYMUDv5+/ujpqZGdRkOl5iYiN27d3vlRgrNtbSV3/PPP4+BAwdi9erViqr7KdjfeOMNvPbaa8rqIPJWDNB2qq2t9cju09zgwYMtThzrrd0ncG8rv5b2w1XRhUopsXbtWrzxxhsuf2wiuofrQNvJz89P+bAduc6SJUtgMpmwbNkyCCGwZcsW/UTQK1euxObNm7F69Wps2rTJpa+L3/3udzZfi+62ftVbxMfHIy8vjxOKPAgDtB1qa2sRGRmJ2tpa1aWQCy1duhQAsGzZMvj4+GDIkCFNdiR6/vnnsXHjRrzwwgsureu///u/rV7+yiuvICwsjJspEDkZA5SoDZYuXQqTyaRvKK91n+Z+/etfu7QmjoQQqcVjoG1UV1eHgIAA1WWQASxfvtwiPFVYu3YtXn/9dYvL169fj9LSUu5KZCB5eXmIi4tTXQY5GAO0Derq6uDv7w8/Pz8O33o5bTs/I3j99dfx29/+1mon+uabb6K0tJQn0yZyIgZoK+rr6+Hv748ePXowPMlw1q5dCyEEfv/731tc9+abb+I3v/mN64si8hIM0Fb06NEDUkrU1dWpLoUU2rZtmyFPqP36669DSmlzE4U1a9awCyVyEgYoURstW7bMMMO3zbW0nd+aNWvw9ttvu7YgIi/AACVqxbZt25CVlYV3331XdSk2/f73v8crr7xicTz0rbfegpQSV69exYYNGxRVR8C9iUSTJ09GQUGB6lLIQRigRC3Yvn07srKysG3bNtWltOq1116DEALr16+3ev2LL77IEFUoPj4eV65cUV0GORDXgRLZoJ2NpaUzshjJunXrYDKZrF739ttv27yOiOzDDpSoBYsXL3aL7lOzfv16lJeXW10DumHDBpdv9kA/yc/Ph5QSsbGxqkshB2GAEnmgl19+2WqIvvjii9i4cSN3MSJyAAYokRU7duzA119/je3bt6supd3Wr18PKaXVjRS0LvSFF17Apk2bFFVI5BkYoETN7NixA0uWLFFdBhEZHAOUyIpnn33WLbtPc2+++SaKioqsbqSwceNGXLhwgV0oUQcwQInM7Ny50+O6T26kQOQcXMZC9KNdu3bhxIkTHjXBRus+X3rpJQghmpyzdNOmTVi1ahU2b96M559/3iX1eNJzS8QOlMjDabsR5efnW91IYdWqVU7folBKCSklZs2aBSEEhBBYtGgRpJR48sknnfrYRM7CDpToRwsXLsTChQtVl+FSmzZtgpQSK1euBACHbphv3m3Onj0b+/fvBwAcOHAAM2bMcNjjEKnCACXyEhs2bNA7QR8fH/3yzZs3d3iXouZDsz4+PpgzZw7++Mc/6pft378fM2fO7NDjEBkJh3CJvMiLL74IIQQ2btzY5PItW7a0u/vUwlhKiblz5+pDs0II7Nu3Dx999FGT2zA8ydOwAyXyIloX2hHa9y9YsACpqan65Xv37sUzzzzTofsmcifsQIm8UHt3IjLvJBctWgQhBFJTU7Fnzx79coYneRsGKJGX0fbCbctGClo4LlmyRB+enTBhgn75vHnzXFQ1kfFwCJe8RvPJM9plACwu90bmQ7va8/Hcc89hx44dAID33nsPixYtUlEakSGxAyWvsG/fPoshxtTUVAghsGDBAkVVqbVp0yZcuHABmzdv1peyaF2mdgq37du3Nxm6JaKfsAMlrzVv3jxIKXHkyBHVpSi1atUqrFq1CsC92bjLly9XXBGRe2AHSl7FfDJMamqq13afGm0jBe2L4UnUduxAyWt8+OGH+PDDD1WXQUQegh0oeY1f/epXTbqtPXv2qC6JiNwYA5S82rx587B7927VZRCRG+IQLnmFOXPmYPbs2RaXazvpsBslovZiB0pewdoyFiKijvBpz76YPj4+twBcc145REREhhIlpexp7Yp2BSgRERHdwyFcIiIiOzBAiYiI7MAAJSIisgMDlIiIyA4MUCIiIjswQImIiOzAACUiIrIDA5SIiMgODFAiIiI7/D9aZlIR2307fgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 13.0\n",
      "LD for BEAM SEARCH- 13.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C22H30N4O5S/c1-3-22(2)20(28)26(21(29)23-22)24-19(27)16-10-12-25(13-11-16)32(30,31)18-9-8-15-6-4-5-7-17(15)14-18/h8-9,14,16H,3-7,10-13H2,1-2H3,(H,23,29)(H,24,27)/t22-/m0/s1\n",
      "\n",
      "\n",
      "PREDICTED-- C22H30N4O5S/c1-3-22(2)20(28)26(21(29)23-22)24-19(27)16-10-12-25(13-11-16)32(30,31)18-9-8-15-6-4-5-7-17(15)14-18/h8-9,14,16H,3-7,10-13H2,1-2H3,(H,23,29)(H,24,27)/t22-/m0/s1\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 22H30N4O5S/c1-3-22(2)20(28)26(21(29)23-22)24-19(27)16-10-12-25(13-11-16)32(30,31)18-9-8-15-6-4-5-7-17(15)14-18/h8-9,14,16H,3-7,10-13H2,1-2H3,(H,23,28)(H,24,27)/t22-/m0/s1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C19H29N5O/c1-5-13(3)24-18-16(11-21-24)15(10-12(2)22-18)19(25)23-9-7-6-8-17(23)14(4)20/h10-11,13-14,17H,5-9,20H2,1-4H3\n",
      "\n",
      "\n",
      "PREDICTED-- C19H29N5O/c1-5-13(3)24-18-16(11-21-24)15(10-12(4)22-18)19(25)23-9-7-6-8-17(23)14(4)20/h10-12,14,17H,5-9,20H2,1-4H3\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 19H29N5O/c1-5-13(3)24-18-16(11-21-24)15(10-12(3)22-18)19(25)23-9-7-6-8-17(23)14(4)20/h10-12,14,17H,5-9,20H2,1-4H3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 8.0\n",
      "LD for BEAM SEARCH- 8.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C20H17BrCl2N2O4/c1-11-14(22)3-2-4-17(11)25-9-12(7-19(25)27)20(28)29-10-18(26)24-16-6-5-13(21)8-15(16)23/h2-6,8,12H,7,9-10H2,1H3,(H,24,26)/t12-/m0/s1\n",
      "\n",
      "\n",
      "PREDICTED-- C19H15BrCl2N2O4/c20-12-4-5-16(15(22)8-12)23-17(25)10-28-20(27)11-6-18(26)24(9-11)14-3-1-2-13(21)8-14/h1-h,7-8,11H,,,,-11H2,(H,22,2,)/t1/-/m//s1\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 19H15BrCl2N2O4/c20-12-4-5-16(15(22)8-12)23-17(25)10-28-20(27)11-6-18(26)24(9-11)14-3-1-2-13(21)8-14/h1-h,7-8,11H,,,,-11H2,(H,22,2,)/t11-/m//s1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 72.0\n",
      "LD for BEAM SEARCH- 72.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C20H19BrN4O3/c21-15-5-3-14(4-6-15)20(8-1-9-20)19-24-18(28-25-19)13-2-7-16(23-12-13)17(27)22-10-11-26/h2-7,12,26H,1,8-11H2,(H,22,27)\n",
      "\n",
      "\n",
      "PREDICTED-- C20H19BrN4O3/c21-15-5-2-13(3-6-15)20(8-1-9-20)19-24-17(28-25-19)14-3-6-16(23-12-14)17(27)22-10-11-26/h2-7,12,26H,1,8-11H2,(H,22,27)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 20H19BrN4O3/c21-15-5-2-13(3-6-15)20(8-1-9-20)19-24-17(28-25-19)14-3-7-16(23-12-14)17(27)22-10-11-26/h2-7,12,26H,1,8-11H2,(H,22,27)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 8.0\n",
      "LD for BEAM SEARCH- 7.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C12H20N4OS/c1-9-7-16(5-6-17-9)12(13)14-4-3-11-10(2)15-8-18-11/h8-9H,3-7H2,1-2H3,(H2,13,14)\n",
      "\n",
      "\n",
      "PREDICTED-- C12H20N4OS/c1-9-7-16(5-6-17-9)12(13)14-4-3-11-10(2)15-8-18-11/h8-9H,3-7H2,1-2H3,(H2,13,14)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 12H20N4OS/c1-9-7-16(5-6-17-9)12(13)14-4-3-11-10(2)15-8-18-11/h8,9H,3-7H2,1-2H3,(H2,13,14)\n"
     ]
    },
    {
     "data": {
      "image/png": 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3OXjwILfyIyKXM2SACiFaDc+7d+9CCOG0Lz8/P4vH9Pf3R21tLd+oDUjbyo+IyFUMF6CNjY1tOhuLtkuRs75sDV/U1tYiMDCQIUpEHqmurs7qWlAA6N69OzdTMGOoAG1reKrGECUiT2ZrQwWuA23KUAEK3Bu+NfLpzPz9/VFdXa2HKBGRp7E2ichTw7MjjZBhAtRduk/g3obL1dXVADj7k4i8h6e835kfrhNC2P1zGSJAtfA0evdpLiAgAFevXkVQUJDHvKiIiFriCcdAtdDUvkwmk92b4ygPUJPJ5Hbhaa6mpgZBQUGqyyAicig/Pz+PHMbV9lY3mUyQUnZoZznlAQoY/7inLQEBAaiqqlJdBhGRS7hzB2q+vr8jXac59zjoaGCBgYGorq7u8CcZIiJyDm3YFnBceAIG6EB9fHzcsvs0V11djeDgYB4LJSKPUFdX12TzeHffnc0Z4QkoDlCTyQRfX1+VJTiMFqJERJ5COw7q5+cHIQR++OEH1SW1mXnoa//v6FFCZQHqSeEZGBiIyspKAJ4zzZuIvJO1brO+vl6/PDQ0FN9//72hu1LzmbbOrFFJgGrh6ePjA5PJpKIEp6iurtZP0k1E5G6klPD394cQArdv37a6rd/333+P0NBQPaCM1pU663inNco6UE8Lz6CgIFRWVqKqqgohISGqyyEiajOtmwwICEB9fb1+0gxbe+JqHej999+Pbt266SGqqnkw74Z9fX0dskSlLVweoNq6T08KT01QUBAqKipUl0FELmTkocy2kFIiMDAQQggUFRVBSmn1bFTW/PDDD5BSomvXrgCArl274s6dOy59TqSU8PX11TdFcHbXaU75LFxPExwcjMrKSrf+gyKitpFSYsCAARBC4OLFi6rLaTctPGtra1FdXQ1/f/8O3d8//vEP3Hfffbj//vshhNDD1Fm08GxoaGgydOsqLg9QTxu6taayspLDuEQeTkqJgQMH6sH50EMP4eLFi27z4bl5eAYEBDjsvu/cuYOf/exnepD+85//dMrz4uvrq/T5dmmAetLM27Zw96EdImrKfBPygQMH4qOPPmpy2YwZMyCEwOXLl/XbG41Wa1BQEK5evaof+3Q0rfvs0qUL7rvvPggh8K9//avV90Vr52e2RTvW6erOU+OyR/XkY5/NBQcHIzc3F0II9OzZU3U5ROQggwcP1meffvTRRxgwYECT67UOtH///gCA/v37Izc31xAfprUagoODIYRAQUGBU4KzOa371ML0Zz/7mR6m1mrs3Llzk83ejbzVq0sCVBun9ibBwcG4desWAGN+CiWi9tH+jnNycvRjn63Jzc3F1KlT9SDIz893dpk2hYSE6DVow7cqaF1oly5dLK7r0qULGhsbcffuXT10fX190alTJ0OGqMs6UG849mlNZWUlQkNDVZdBRHbSgnPIkCFITU1FYmJiu75f60Dj4uIQHx+PgoKCJvfrbObdb0VFhWHPHqXVePfu3Sbnhm5oaIAQwpAh6vQA1canvTE8Q0JC2IUSubmhQ4ciJycHOTk5NsOzLUO0Wuf385//HAUFBYiNjUVhYaEzSm5Sl9Z55ubmGnq70S5duqChocHqdY2NjcqOc7ZEaUVGOC7gChUVFYbpQj3xOX/yySdx4MABAPygQo7R3teR+VKW1ia/aOEJALGxsfpEHkf+bWr307NnT1RVVaGiosLQ4dkWDQ0NhjsU6LIAbf7CMJlMEEIY7gnxRAkJCbh06RIuXboEIQQeeughjwgaKSUOHjwIIQRmzpyJTz75BLNmzfKIn43UGj58OM6ePQsAOHfuHAYPHtzi7S9cuAApJR588EE8+OCD+jHP3Nxcm99TWFgIKSWio6MRHR2tf4+2mYG9tP1qKyoqUFFRoU8ccndeOYSraR6URp5Z5WjmQ7mulpubiwceeABSSjzwwAO4cOECLl26hAEDBrh10Hz22Wd46qmnANzrQKWUOHDgAD7++GOGKNnFUV3gpUuXIKVEQkKCPgtXu39brl27pj/2mDFjIIRAcXGxXfX36tXLI3dEM2IHanXNja2vpKQkaQ+TySR9fHykyWRqcnljY6P08fGx6z7dwa1btyQAGRISoqyGy5cvSwCyf//++mUXLlyQAORDDz0kTSaTxe/F6P70pz9JAHLatGkW1+3fv18CkLNmzVJQGbkrk8kkk5KSJAAJQJ45c8Yh9xsfHy8ByNzcXBkXFyfz8vLa9H0RERESgCwuLm7z32doaKhe/82bNztSthKdOnWSAOTdu3ctrjOZTFIIIRsaGlxe14+5ZzUTXTqE23zXCE+ZXCStfLLULjNfzqJCQkICTCYTLl26pF/24IMP4rvvvsOFCxcghEBiYqLhj41q9R06dAjTpk3D1KlT8emnn1rcbubMmdi/f7/F9xFZo70+Ro4ciezsbJw+fVprFhxy/9oM3Pj4eADQZ+GavwlbU1xcDCklRo0aBSEESkpKrH5P83/fuHEDUkq3XH+uzb7t3LmzvjWf9mXYPQRsJau1L3s7UCnvdZsAbHac7tYFaaqqqmRAQECTyyoqKiQAGRwcrKiqn1y+fFkmJCS0eJvz589LAHLQoEGG7EgPHTokAchf/OIX7fq+ffv2SQBy9uzZhvuZSD2TySRHjBghAcisrCyXPnZMTIzeLRYWFrbp9RkWFqZ/T0lJiZRSyl69ekkAsry83Nklu5yvr6/+86roPDUtdaCdrKaqE2jHPM3X92gaGxv1Kcyu2kXfEWpqahAUFGR1Nw+jnJklPj5e31bMlkGDBkFKifPnz+sd6blz55T/LqSU+OKLL7Bp0ya7usjZs2cDAObMmQMA2Ldvn0PrI/clpURycjJOnz6NrKwsjBgxwqWPr60FjYmJQUxMDADg6tWriIyMtPl3V1paqv9/eHg4srOzAQBlZWXo1auXkyt2PVtLWozEpctYtCFba2+G2lZ/7iYgIADV1dWqy7AqNzdX31KsLRITE5GTk4Pz589j6NChyoY/teAUQuCJJ57oUJDPnj0bH374IXx8fDiUSwB+Cs9vvvkG33zzjcvD05w2EzcyMhIAEBUVhaKiola/r7S0FMOGDcO5c+fQu3dvZ5dJNig5H2jzY6Ha6WjcSU1Njc2tsLSTa6uWkJDQavfZnNZ95uTkQAiBYcOGuTRIjxw5gkmTJgEAJk2aBCkl/vznP3foPufMmYPp06fjmWee4TFRL6b93kePHo23335bP/ZpBNeuXUNUVBSAeyGqHQPla9XYlGykIKXl3ri+vr76shajv2hqamoQHR0NKaVF92mkU5m1twPVDB48WP/j3bFjB4QQGD58uNP+oM2PKTz++OM4cuQIJk+ejC+++MJhjzFnzhxMmzYNQgjMnTvX8K8xciwpJVJSUpCZmYnMzEyMGjVKdUlWaWtA+/bti8jISH0CERmTywPUfP2ntTcxW8dJjaK2ttZm51lVVWWY8ATadvyzNdpQ7tatWyGEwIgRIxwapMeOHdMXkD/++OMOuU9bnn76abz//vv44IMPMH/+fIaol9DCc/369UhOTlZdTptpXWifPn1Ul0I2KNvKT+tC3fFNzN/fHzU1NU0uq6qqQnBwsGGGb/Py8iCEsKsDtSYpKQlnzpxBdnY2hBA2h77a8/s8duwYJk6ciIkTJ0JKiS+//NIhtbbk6aefhpQSkydPZoh6OO2D3pgxY7B+/XqMHj1adUkOFxYWhvLyctVleC0lAap1oS0N5brjG1tgYKAhwlN77uLj41vcSqy9kpKSIKVEVlaW1eszMzORkpJi8btr6Xf56KOP4quvvnJYjW01b948TJ48GQsWLHDL1xq1buzYsRBCYN26dR4ZnqSesg60pa38Ghsb0blzZ8O9sUkp4efnZ9F9VldXG2avyfz8fCQkJDg8PM2NGDECp0+ftnpd8xA9efIkxo4da/V3OWHCBBw7dswpNbZVamoqQ9SDpaWlISUlRXUZ5KGUno2lpWUtRgvRuro6CCFsnsE9MDAQVVVVri3Kiri4OKcFZ1tlZmZizJgx+r/T09Mxbtw4hRVZN2/ePH3i0qJFiwzzWiNqC09d/+lOlJ9gzdr6T+3Y6J07d9C5c2dFlVny8/NDbW2txeUBAQGGCM/8/HwIIZCQkKAsDJKTk5GRkaHkse01f/58TJgwAYsWLVJdCrkAPyiRoygPUE1LL2rVL/i6ujr4+/tbva66utowZ3iPi4tDXl6ePoyrmurfW3ssXLgQu3btUl0GucDo0aNx6tQp1WWQBzBEgGpdaEtDuar16NHDovvUtvIzgoKCAsTHx6Nfv34wmUxKh3FHjx6NdevWNRnGdVfma1TNLyP3MHbsWLcbESH3oTxAhRCQUuJf//qXRYh26tQJd+/eVVjdPT169EBdXV2Ty7SdiIywlZ+UEjExMXr3qQ3jqpSSkuL2b1zbt2/X16guW7YMALBlyxasXLlScWVEZASG2rFA60TNZ+d26tRJP7WNis3N6+vr0adPH4sADQgIgMlkUr7hemFhIWJjY/V/x8XFGaIuAMjIyMDYsWNVl9Fhzz33HLZt2wYAWLFiheJqqK1OnjyJRx55RHUZ5MGUd6Aa8/1wmw+RNTQ0KJuR2717d4vwBFreC9eVYmJiYDKZcOXKFQDAlStXlHefnmTx4sXYunWr6jKIbAoLC8ONGzdUl+GVDBOgwL0Q1YZym1OxrKW+vh5+fn4Wl2t74TZfD6qC1oHGxsZCSom8vDzVJXmUHTt2YNmyZfrrjht8E5HGUAFqrvmxUG1ZS5cuXVzy+PX19QgPD0d9fX2Ty2traw0TnsC9DrSwsBDAvWUskydPVhaiycnJ+Prrr/V/axsqSCmRlpampKaOWLJkiX7GjmXLluHdd9+FEAIrV65kiLoxI28m317l5eVcC6qQ4QJU60JVz7zt0aOHRXgCsLoTkVH069cP+fn5qsvwOEuXLsW2bduwfPlySCkxZMgQrFq1SnVZRKSY4QLUXPNP+apn5dbW1trciYi8A2fhup8xY8Y0GRkhchTDBqhR1n8SNbd8+XJs2rRJdRlEpJghA9TX11fvNI0yaaOurs4Q3aet58Ioz1NzRq2rI959910O4bo5T3tNkhqGDFDg3nDtnTt3IITQZ9866gtAu25fV1eHiIgISCmt7oXrKkVFRYiOjra4vLCwEEIIxMfHu76oFmRkZEAI4RFrQTUrVqyAlBKbN29WXQq1wcmTJ62eyiw5OdmjtvPr3bs3l7IoYNgABX465tnY2KjvCNPRr65du+KHH35o1/fY2gfX1SIjI3H16lXVZbRZSkqKW86+Jc+Snp7O84GSUxg6QM2ZD+t2xJ07d9CtW7c237579+5Ku05ztjpQd8AhM1LF0ycRlZeXIzQ0VHUZXsnwAaqtAW1oaND/35Vf5ktZjBICRqmjrYx6PlAioo4wfIAagZ+fH65fv46AgADl4dW8C22+F67RPPLIIxzGJSKPZKjN5I1Om4mrakg3MjLSYqP4mJgYFBQUYOLEidzGz8FUncCAHCs9Pd3jf4/l5eUe/zMaETvQNjLCDkQtHQMtLCw03Czc5lR37+2xY8cOPPfcc6rLIAfw9GOgAGfhqsIAbQd/f3/U1tYaMgi084Ea1cmTJzF+/HjVZbTJjh07kJ6eju3bt6suhRwgIyPD5lKWrKwsBRWRp2CAtlNtba0hTmPWnJE70EceeQR//etfVZfRJjt37kR6ejp27NihuhQiC564MYk7Y4C6kcjISFy7ds3i8piYGEgpuZF8B+3atQvPPvus6jKIrJJSok+fPhBCoKysTHU5BE4iajd/f3/9WCgnmXiehQsXsvv0AqdOnXKrU5pp4VlWVobS0lKEhYU1uZ7HP9VgB2qnmpoaBAYGcjiFiJxKSomIiAiUlZWhpKTEIjxJHQZoB9TW1iIoKIghSmRw7vg3qh3vjIiIQGlpKUpKShAeHm71NqQGA9ROAQEBqK6uRk1NDYKCglSXY3hjx4419ESiXbt24dixY9i5c6fqUsgJUlJS3GYpixaKkZGREEIgKysLUsom4andJiwsDEIIDuEqwmOgHRAQEICqqipD7wRkNEY9brxgwQIsWLBAdRnkQkY9G0tUVBSKi4tRVFSEvn37Wr1NeHg4ysvLAQBlZWXo1auXK0ukH7ED7aDAwEBUV1erLsMt/PWvfzXkWtA9e/ZACIFFixapLoW8mNZVFhUVQUppMzy1D6GlpaWQUqJ3794urpQ0DFAH4bEI97ZgwQLs2rVLdRnkhbT3jujoaAghUFRU1OLt+/Tpg+zsbE4mMgAGqANUV1dDCIHg4GDVpbgFI33Q2LNnD44cOcLw9BJGeu0B9+qJiYmBEAJpaWn6sU9rt9NYW8ZCajBAHSAwMBCVlZUAjPcHajRpaWmYMGGC6jIAAKmpqTzu6eHMR4ZSUlIghEBmZqZh/k5jY2Nx4sQJSCkRFRVlcX3zmbhkLAxQB6qurkZISIjqMogI98Jn7NixEEJg/fr1kFLqmyckJyfj1KlTyoJUC8bCwkKbJ4jQjoNqM3GbL2Eh9RigDqKtB9U6UfqJlBJpaWlNJhA1P3G5KvPmzcOePXuUPT45nvZ6Gjt2LNLT05Genq5vJp+ZmYnk5GQA90JUCIHTp0+77HWoPUZcXByEECgsLLR528jISJSUlOD69evo06eP02uj9mOAklOdPHkSQgj87ne/g5QSJ06cwIkTJyCE0L8ee+wxi0A1f0Nz1hvb3LlzvTo8bT3f7kxKiXHjxiEtLQ0nT56ElBIpKSkWt9O6TyklRowYgZEjR0IIgTNnzuj34+i6pJSIj49HQUEBCgoK9OOfzW+nKS4u1rfwI2NigJLTjRkzBmlpaQCAcePG6W8mR48eBQAcPXq0SaBqX1OmTMHhw4fxi1/8okmYOiJgU1NTMX/+fI8IDXtIKbF69WqL5/zdd99VXZrdpJQYP348/uu//gtjx45t1/eePn0aSUlJGDFiBLKzszF8+HCcPXvWYXUlJCRACIErV660eLuoqKhWZ+GScTBAyWkyMjKwdu1anDx50uZtHn30Uaud0OHDh/GXv/wFTzzxBA4fPoypU6fi0KFDTd7sn3rqKRw8eBDTp0+32cG21Fnt3bvXaycRvfDCC9i8eTPeeecd/Tlavnw5VqxY4XYhqtU/fvx4/YOaPc6cOQMpJZKSkizuuyO19e/fH/n5+cjLy4OU0mLjFfNlLOnp6VZn4ZIxcSciFzHqDjyqHD9+HBMnTsSjjz5q9frJkydbfePSLvvss88wbdo0/OlPfwIACGH7s+CcOXPwwQcfAAB8fHzw/vvvY/78+U3u0xt/N++88w5WrVql/3vLli1u2ZFPnDgRx48fx4kTJzBu3DiH3Gd2djaGDh2Kc+fOAQDOnTuHwYMHt/t++vfvj7y8POTm5qJfv35WbxMTE4Nr167h6tWrDE83ww7UScw/ud66dQuhoaEWl3sqKSUyMjLw6quvWnSfUkocP34cEyZMwKOPPopjx47Z9Rj/9m//1mLH+dFHHwEAfvnLX2L69OkQQuCZZ57BBx98gLlz5+rHP7WlLJ7+OzHnCT9r87+jY8eOOSw8NWfPnoWUEoMHD8aQIUOQk5OjP7b5f1tz+fJli5PdN6//6tWrVpexkMG1NvRl/pWUlCSpdRUVFRKADA4ObnL5jRs3JAAZGhqqqDLny8jIkADk6NGjLa47ceKEBCDHjx/v8ro+/PBD+atf/crqdbt375YLFiyQJpPJxVWpsXr1arlhwwbVZdjFZDJJk8kkJ06cKAHIo0ePuryGQYMGyfPnz8uHHnpI/v3vf7frPmJiYiQAWVBQ4ODqyNF+zD2rmcgO1EmCgoJQUVHR5LLQ0FD9rAnSA7qA5jIzM5GSkoLk5GRkZGRYvc3YsWNx/PhxF1f2EymtjwDs3r2be+G6gccffxxCCBw9ehRffvmlkk05zp8/j0GDBuG7777D7NmzceHChTb/PWu3szULl9wLA9QJgoODLcLT3M2bNz12K67k5GSrp41KS0vDf/zHfyg7pdmcOXMwbdo0CCEwd+7cJtdps3G96VRmL7zwAjZt2mRxuZE/2Gm1HTlyBFJK/PznP1dc0T0DBgyAEAIXL15s8XbSbBkLeQYGqBNUVlZ63Y5Ep06dwpo1a6yGp1HelJ9++mlIKfH+++9b1LRr1y4sWrTIMLWqIKVscRau+dCVK2vSHm/SpEl49dVX8dhjj7ns8Vvz3Xff6TXOmDFDD9HmQ30AEB8f3+IyFnJDtsZ2rX3xGGjbVFRUyKCgIKvXacdBe/Xq5eKqnCczM1M+/PDDVq9LS0uTY8aMcXFFLdu7d6+cO3euxTHPnTt3yoULF3rFsdDVq1dLAPKdd96RUt47trh8+XK5ZcsWm9+zcOFCCUACkDt37tSPRzrT5MmTJQB5+PBhpz6OoyUkJOjPFQCZm5uruiSyE4+BktNkZWXhN7/5jdWTE7dlHagqe/fubbKURbNr1y4sWbJEQUWutXHjRjz//PP6v1euXIkhQ4Zg+fLlNr9n586d+hvHsWPH9PW4qampDu9KpVnndvjwYUyePNmh9+9sly9f1odsrc3CJQ9hK1mtfbEDbRutA7X26fzGjRseMwv3m2++kQBsdp/u2Mm999578tlnn3XL2lWYO3eu3mXt3bvXIV2pyWSSU6ZMkQDk559/7qBK1YiPj5eXL19WXQZ1ADtQBaqqqtCzZ08AP31IuXnzJnr16qW4Msc4ffo0Hn74YYwYMcKi+5Q/rgMdM2aMouraTlrpnN577z0sWbLEq4+HtpXWfT799NOYO3eu3pXu27fP6nHAlmi3mTp1Kg4fPozPP/8cU6ZMcfaPQGQ/W8lq7YsdaPvdunVL/4Tes2dP1eU4RFZWlhw+fLjV61paB2o0e/bskfPmzbPomLZv3y4ByMWLFyuqzDP88pe/bHIccP/+/S12p1OnTpWfffaZCyskal1LHSi38nOykJAQj+pkzpw5g5EjR2L48OEW17VlHajRpKamAkCTs7IsXrwYANzmZ2gLKV2/XaG2GxRwb0eoWbNmAQAOHDiA6dOnw8fHp0ldn332mUvrI+ooDuFSuwwfPhxSSpw+fdrq9bbWgRrRvHnzsHv3bgCWQ7mLFy/G9u3bPeLDj5QSL730EjZs2KCshj/+8Y/6Uo+ZM2dCCIGDBw/iqaeewqeffqqsLmeTbRy+JvfEACWHaGkdqNGlpqZaXQO6fft2PPfcc4qqcpw1a9bg//7v/1SXAeBe96mFys6dO/WTAXiq/v37QwiBvLw81aWQE3AI18FUDJWpdurUKSQnJ2PUqFGqS2k3bSmLdlqzXbt2WdzGnX+nUkq89dZbeOutt1SXQuRx2IE6UFVVldftQAQAo0aNgpQSmZmZqkuxy/z5861u47dkyRKMHj0ay5Ytc8thOCkl1qxZw/BUKDc3l2tAPRg7ULKqeWC4awfWVgsXLsTChQutdpt/+MMfAABbt251q+fh5ZdfRmRkJF566SXVpRB5JHagDlJVVYXg4GDVZThETk6Ovp5PCIFhw4apLskldu3ahWeffbbJZUuWLMHWrVvxhz/8AStWrFBUWfu5Y8dM5G4YoA5QXV2N4OBgBAYGorKyUnU5HXL+/Hn9BNNSSvztb3/Tr/OWN+XmMyeXLl2KrVu36tcZnZQSL7/8Mv73f/9XdSlEHo0B6iCBgYGoqqpSXUaHnD9/HoMHD25y2dChQ3H27FlkZ2dbXfvpSRYuXIjx48dDCGGxH+7SpUsxbNgwrFy5UlF1bSOlxCuvvILw8HB9+QoROQePgTpAQECA24enZtCgQcjJyVFdhjKLFi2CyWRCenq6282+1cKzd+/e+Pd//3fV5RB5PHagHVRdXY2goCDVZZCDvffeexZrQJcvX44tW7YYdhj3tddew5tvvqm6DLIiISEB+fn5qssgB2OAdoBR30g7ylN/rrbSdiGyZsuWLVi5cqXhniOtnv/5n//Byy+/rLgaIu/AALVTTU0NhBCIjY1FdXW16nIc5ttvv8WQIUNUl6Gcra38VqxYgSFDhmDVqlWKKrMkpcRvf/tbhISEMDwNKDc3F/369VNdBjkBA7QD/P39PSo8qanWtvIzQheqhee6detUl0LkdRigdqipqUFgYKDqMhwuMTFRn0Bkfsqes2fPYtmyZcjOzlZcoRrWutCBAwdi1apVykN07dq1WLduHd544w28+uqrSmsh8jYMUDv5+/ujpqZGdRkOl5iYiN27d3vlRgrNtbSV3/PPP4+BAwdi9erViqr7KdjfeOMNvPbaa8rqIPJWDNB2qq2t9cju09zgwYMtThzrrd0ncG8rv5b2w1XRhUopsXbtWrzxxhsuf2wiuofrQNvJz89P+bAduc6SJUtgMpmwbNkyCCGwZcsW/UTQK1euxObNm7F69Wps2rTJpa+L3/3udzZfi+62ftVbxMfHIy8vjxOKPAgDtB1qa2sRGRmJ2tpa1aWQCy1duhQAsGzZMvj4+GDIkCFNdiR6/vnnsXHjRrzwwgsureu///u/rV7+yiuvICwsjJspEDkZA5SoDZYuXQqTyaRvKK91n+Z+/etfu7QmjoQQqcVjoG1UV1eHgIAA1WWQASxfvtwiPFVYu3YtXn/9dYvL169fj9LSUu5KZCB5eXmIi4tTXQY5GAO0Derq6uDv7w8/Pz8O33o5bTs/I3j99dfx29/+1mon+uabb6K0tJQn0yZyIgZoK+rr6+Hv748ePXowPMlw1q5dCyEEfv/731tc9+abb+I3v/mN64si8hIM0Fb06NEDUkrU1dWpLoUU2rZtmyFPqP36669DSmlzE4U1a9awCyVyEgYoURstW7bMMMO3zbW0nd+aNWvw9ttvu7YgIi/AACVqxbZt25CVlYV3331XdSk2/f73v8crr7xicTz0rbfegpQSV69exYYNGxRVR8C9iUSTJ09GQUGB6lLIQRigRC3Yvn07srKysG3bNtWltOq1116DEALr16+3ev2LL77IEFUoPj4eV65cUV0GORDXgRLZoJ2NpaUzshjJunXrYDKZrF739ttv27yOiOzDDpSoBYsXL3aL7lOzfv16lJeXW10DumHDBpdv9kA/yc/Ph5QSsbGxqkshB2GAEnmgl19+2WqIvvjii9i4cSN3MSJyAAYokRU7duzA119/je3bt6supd3Wr18PKaXVjRS0LvSFF17Apk2bFFVI5BkYoETN7NixA0uWLFFdBhEZHAOUyIpnn33WLbtPc2+++SaKioqsbqSwceNGXLhwgV0oUQcwQInM7Ny50+O6T26kQOQcXMZC9KNdu3bhxIkTHjXBRus+X3rpJQghmpyzdNOmTVi1ahU2b96M559/3iX1eNJzS8QOlMjDabsR5efnW91IYdWqVU7folBKCSklZs2aBSEEhBBYtGgRpJR48sknnfrYRM7CDpToRwsXLsTChQtVl+FSmzZtgpQSK1euBACHbphv3m3Onj0b+/fvBwAcOHAAM2bMcNjjEKnCACXyEhs2bNA7QR8fH/3yzZs3d3iXouZDsz4+PpgzZw7++Mc/6pft378fM2fO7NDjEBkJh3CJvMiLL74IIQQ2btzY5PItW7a0u/vUwlhKiblz5+pDs0II7Nu3Dx999FGT2zA8ydOwAyXyIloX2hHa9y9YsACpqan65Xv37sUzzzzTofsmcifsQIm8UHt3IjLvJBctWgQhBFJTU7Fnzx79coYneRsGKJGX0fbCbctGClo4LlmyRB+enTBhgn75vHnzXFQ1kfFwCJe8RvPJM9plACwu90bmQ7va8/Hcc89hx44dAID33nsPixYtUlEakSGxAyWvsG/fPoshxtTUVAghsGDBAkVVqbVp0yZcuHABmzdv1peyaF2mdgq37du3Nxm6JaKfsAMlrzVv3jxIKXHkyBHVpSi1atUqrFq1CsC92bjLly9XXBGRe2AHSl7FfDJMamqq13afGm0jBe2L4UnUduxAyWt8+OGH+PDDD1WXQUQegh0oeY1f/epXTbqtPXv2qC6JiNwYA5S82rx587B7927VZRCRG+IQLnmFOXPmYPbs2RaXazvpsBslovZiB0pewdoyFiKijvBpz76YPj4+twBcc145REREhhIlpexp7Yp2BSgRERHdwyFcIiIiOzBAiYiI7MAAJSIisgMDlIiIyA4MUCIiIjswQImIiOzAACUiIrIDA5SIiMgODFAiIiI7/D9aZlIR2307fgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C12H13N3OS/c1-16-11-3-2-9(12(13)17)6-10(11)7-15-5-4-14-8-15/h2-6,8H,7H2,1H3,(H2,13,17)\n",
      "\n",
      "\n",
      "PREDICTED-- C12H13N3OS/c1-16-11-3-2-9(12(13)17)6-10(11)7-15-5-4-14-8-15/h2-6,8H,7H2,1H3,(H2,13,17)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 12H13N3OS/c1-16-11-3-2-9(12(14)17)6-10(11)7-15-5-4-14-8-15/h2-6,8H,7H2,1H3,(H2,13,17)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C17H22ClN3O/c1-3-9-20(10-4-2)17(22)15-11-19-21(13-15)12-14-7-5-6-8-16(14)18/h5-8,11,13H,3-4,9-10,12H2,1-2H3\n",
      "\n",
      "\n",
      "PREDICTED-- C17H22ClN3O/c1-3-9-20(10-4-2)17(22)15-11-19-21(12-15)12-14-7-5-6-8-16(14)18/h5-8,11,13H,3-4,9-10,12H2,1-2H3\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 17H22ClN3O/c1-3-9-20(10-4-2)17(22)15-11-19-21(13-15)12-14-7-5-6-8-16(14)18/h5-8,11,13H,3-4,9-10,12H2,1-2H3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 1.0\n",
      "LD for BEAM SEARCH- 0.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C23H27NO5/c1-14(2)17-6-9-20(10-7-17)24-23(27)16(4)29-22(26)13-19-12-18(15(3)25)8-11-21(19)28-5/h6-12,14,16H,13H2,1-5H3,(H,24,27)/t16-/m1/s1\n",
      "\n",
      "\n",
      "PREDICTED-- C23H27NO5/c1-14(2)17-6-9-20(10-7-17)24-23(27)16(4)29-22(26)13-19-12-18(15(3)25)8-11-21(19)28-5/h6-12,14-15H,13H2,1-5H3,(H,24,27)/t16-/m0/s1\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 23H27NO5/c1-14(2)17-6-9-20(10-7-17)24-23(27)16(4)29-22(26)13-19-12-18(15(3)25)8-11-21(19)28-5/h6-12,14-15H,13H2,1-5H3,(H,24,27)/t16-/m1/s1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 3.0\n",
      "LD for BEAM SEARCH- 2.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C14H8BrClFNO3/c15-9-6-7(4-5-10(9)16)13(19)18-12-8(14(20)21)2-1-3-11(12)17/h1-6H,(H,18,19)(H,20,21)\n",
      "\n",
      "\n",
      "PREDICTED-- C14H8BrClFNO3/c15-9-6-7(4-5-10(9)16)13(19)18-12-8(14(20)21)2-1-3-11(12)17/h1-6H,(H,18,19)(H,20,21)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 14H8BrClFNO3/c15-9-6-7(4-5-10(9)16)12(19)18-12-8(14(20)21)2-1-3-11(12)17/h1-6H,(H,18,19)(H,20,21)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C23H31N5O3/c1-13-11-28(12-14(2)30-13)22-24-10-16-18(8-23(3,4)9-19(16)26-22)25-21(29)17-7-20(31-27-17)15-5-6-15/h7,10,13-15,18H,5-6,8-9,11-12H2,1-4H3,(H,25,29)/t13-,14-,18-/m1/s1\n",
      "\n",
      "\n",
      "PREDICTED-- C23H31N5O3/c1-13-11-28(12-14(2)30-13)22-24-9-16-17(8-22(3,4)10-18(17)25-19)25-21(29)18-7-19(31-27-18)15-5-6-15/h7,1,113-15,18H,5-6,8-1,11212,1-HH,,H,,2,29)/t11-,14-,11//m1/s1\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 23H31N5O3/c1-13-11-28(12-14(2)30-13)22-24-9-16-17(8-22(3,4)10-18(17)25-19)25-21(29)18-7-19(31-27-18)15-5-6-15/h7,1,113-15,18H,5-6,8-1,11212,1-HH3,H,,2,29)/t11-,14-,11//m1/s1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 32.0\n",
      "LD for BEAM SEARCH- 31.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C13H10N2O2/c16-7-8-5-6-11-12(13(8)17)15-10-4-2-1-3-9(10)14-11/h1-6,8,16H,7H2\n",
      "\n",
      "\n",
      "PREDICTED-- C13H10N2O2/c16-7-8-5-6-11-13(12(8)17)15-10-4-2-1-3-9(10)14-11/h1-6,8,16H,7H2\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 13H10N2O2/c16-7-8-5-6-11-12(12(8)17)15-10-4-2-1-3-9(10)14-11/h1-6,8,16H,7H2\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 2.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C24H23Cl2N5O4S/c1-13-21-23(30-29-13)27-22(28-24(21)35-18-9-7-17(32)8-10-18)14-2-5-16(6-3-14)31-36(33,34)20-12-15(25)4-11-19(20)26/h2-6,11-12,17-18,31-32H,7-10H2,1H3,(H,27,28,29,30)\n",
      "\n",
      "\n",
      "PREDICTED-- C24H23Cl2N5O4S/c1-13-21-23(28-24-10-1--1--1-1--1--2--2--2--2-22-22-22-21--------1------15)31-33(33,33)11-11-1-(1-)----18(18)18-22/h2-6,11-12,17-18,32-32H,7-10H2,1H3,(H,27,28,29,30)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 24H23Cl2N5O4S/c1-13-21-23(28-24-10-1--1--1-1--1--2--2--2--2-22-22-22-21--------1------15)31-33(33,33)21-11-1-(1-)----18(18)18-22/h2-6,11-12,17-18,32-32H,7-10H2,1H3,(H,27,28,29,30)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 63.0\n",
      "LD for BEAM SEARCH- 62.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C17H15NO3/c1-4-18-9(2)13(10(3)19)14-15(18)17(21)12-8-6-5-7-11(12)16(14)20/h5-8H,4H2,1-3H3\n",
      "\n",
      "\n",
      "PREDICTED-- C17H15NO3/c1-4-18-10(2)13(9(2)19)14-15(18)17(21)12-8-6-5-7-11(12)16(14)20/h5-8H,4H2,1-3H3\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 17H15NO3/c1-4-18-10(2)13(1(2)19)14-15(18)17(21)12-8-6-5-7-11(12)16(14)20/h5-8H,4H2,1-3H3\n"
     ]
    },
    {
     "data": {
      "image/png": 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3OXjwILfyIyKXM2SACiFaDc+7d+9CCOG0Lz8/P4vH9Pf3R21tLd+oDUjbyo+IyFUMF6CNjY1tOhuLtkuRs75sDV/U1tYiMDCQIUpEHqmurs7qWlAA6N69OzdTMGOoAG1reKrGECUiT2ZrQwWuA23KUAEK3Bu+NfLpzPz9/VFdXa2HKBGRp7E2ichTw7MjjZBhAtRduk/g3obL1dXVADj7k4i8h6e835kfrhNC2P1zGSJAtfA0evdpLiAgAFevXkVQUJDHvKiIiFriCcdAtdDUvkwmk92b4ygPUJPJ5Hbhaa6mpgZBQUGqyyAicig/Pz+PHMbV9lY3mUyQUnZoZznlAQoY/7inLQEBAaiqqlJdBhGRS7hzB2q+vr8jXac59zjoaGCBgYGorq7u8CcZIiJyDm3YFnBceAIG6EB9fHzcsvs0V11djeDgYB4LJSKPUFdX12TzeHffnc0Z4QkoDlCTyQRfX1+VJTiMFqJERJ5COw7q5+cHIQR++OEH1SW1mXnoa//v6FFCZQHqSeEZGBiIyspKAJ4zzZuIvJO1brO+vl6/PDQ0FN9//72hu1LzmbbOrFFJgGrh6ePjA5PJpKIEp6iurtZP0k1E5G6klPD394cQArdv37a6rd/333+P0NBQPaCM1pU663inNco6UE8Lz6CgIFRWVqKqqgohISGqyyEiajOtmwwICEB9fb1+0gxbe+JqHej999+Pbt266SGqqnkw74Z9fX0dskSlLVweoNq6T08KT01QUBAqKipUl0FELmTkocy2kFIiMDAQQggUFRVBSmn1bFTW/PDDD5BSomvXrgCArl274s6dOy59TqSU8PX11TdFcHbXaU75LFxPExwcjMrKSrf+gyKitpFSYsCAARBC4OLFi6rLaTctPGtra1FdXQ1/f/8O3d8//vEP3Hfffbj//vshhNDD1Fm08GxoaGgydOsqLg9QTxu6taayspLDuEQeTkqJgQMH6sH50EMP4eLFi27z4bl5eAYEBDjsvu/cuYOf/exnepD+85//dMrz4uvrq/T5dmmAetLM27Zw96EdImrKfBPygQMH4qOPPmpy2YwZMyCEwOXLl/XbG41Wa1BQEK5evaof+3Q0rfvs0qUL7rvvPggh8K9//avV90Vr52e2RTvW6erOU+OyR/XkY5/NBQcHIzc3F0II9OzZU3U5ROQggwcP1meffvTRRxgwYECT67UOtH///gCA/v37Izc31xAfprUagoODIYRAQUGBU4KzOa371ML0Zz/7mR6m1mrs3Llzk83ejbzVq0sCVBun9ibBwcG4desWAGN+CiWi9tH+jnNycvRjn63Jzc3F1KlT9SDIz893dpk2hYSE6DVow7cqaF1oly5dLK7r0qULGhsbcffuXT10fX190alTJ0OGqMs6UG849mlNZWUlQkNDVZdBRHbSgnPIkCFITU1FYmJiu75f60Dj4uIQHx+PgoKCJvfrbObdb0VFhWHPHqXVePfu3Sbnhm5oaIAQwpAh6vQA1canvTE8Q0JC2IUSubmhQ4ciJycHOTk5NsOzLUO0Wuf385//HAUFBYiNjUVhYaEzSm5Sl9Z55ubmGnq70S5duqChocHqdY2NjcqOc7ZEaUVGOC7gChUVFYbpQj3xOX/yySdx4MABAPygQo7R3teR+VKW1ia/aOEJALGxsfpEHkf+bWr307NnT1RVVaGiosLQ4dkWDQ0NhjsU6LIAbf7CMJlMEEIY7gnxRAkJCbh06RIuXboEIQQeeughjwgaKSUOHjwIIQRmzpyJTz75BLNmzfKIn43UGj58OM6ePQsAOHfuHAYPHtzi7S9cuAApJR588EE8+OCD+jHP3Nxcm99TWFgIKSWio6MRHR2tf4+2mYG9tP1qKyoqUFFRoU8ccndeOYSraR6URp5Z5WjmQ7mulpubiwceeABSSjzwwAO4cOECLl26hAEDBrh10Hz22Wd46qmnANzrQKWUOHDgAD7++GOGKNnFUV3gpUuXIKVEQkKCPgtXu39brl27pj/2mDFjIIRAcXGxXfX36tXLI3dEM2IHanXNja2vpKQkaQ+TySR9fHykyWRqcnljY6P08fGx6z7dwa1btyQAGRISoqyGy5cvSwCyf//++mUXLlyQAORDDz0kTSaTxe/F6P70pz9JAHLatGkW1+3fv18CkLNmzVJQGbkrk8kkk5KSJAAJQJ45c8Yh9xsfHy8ByNzcXBkXFyfz8vLa9H0RERESgCwuLm7z32doaKhe/82bNztSthKdOnWSAOTdu3ctrjOZTFIIIRsaGlxe14+5ZzUTXTqE23zXCE+ZXCStfLLULjNfzqJCQkICTCYTLl26pF/24IMP4rvvvsOFCxcghEBiYqLhj41q9R06dAjTpk3D1KlT8emnn1rcbubMmdi/f7/F9xFZo70+Ro4ciezsbJw+fVprFhxy/9oM3Pj4eADQZ+GavwlbU1xcDCklRo0aBSEESkpKrH5P83/fuHEDUkq3XH+uzb7t3LmzvjWf9mXYPQRsJau1L3s7UCnvdZsAbHac7tYFaaqqqmRAQECTyyoqKiQAGRwcrKiqn1y+fFkmJCS0eJvz589LAHLQoEGG7EgPHTokAchf/OIX7fq+ffv2SQBy9uzZhvuZSD2TySRHjBghAcisrCyXPnZMTIzeLRYWFrbp9RkWFqZ/T0lJiZRSyl69ekkAsry83Nklu5yvr6/+86roPDUtdaCdrKaqE2jHPM3X92gaGxv1Kcyu2kXfEWpqahAUFGR1Nw+jnJklPj5e31bMlkGDBkFKifPnz+sd6blz55T/LqSU+OKLL7Bp0ya7usjZs2cDAObMmQMA2Ldvn0PrI/clpURycjJOnz6NrKwsjBgxwqWPr60FjYmJQUxMDADg6tWriIyMtPl3V1paqv9/eHg4srOzAQBlZWXo1auXkyt2PVtLWozEpctYtCFba2+G2lZ/7iYgIADV1dWqy7AqNzdX31KsLRITE5GTk4Pz589j6NChyoY/teAUQuCJJ57oUJDPnj0bH374IXx8fDiUSwB+Cs9vvvkG33zzjcvD05w2EzcyMhIAEBUVhaKiola/r7S0FMOGDcO5c+fQu3dvZ5dJNig5H2jzY6Ha6WjcSU1Njc2tsLSTa6uWkJDQavfZnNZ95uTkQAiBYcOGuTRIjxw5gkmTJgEAJk2aBCkl/vznP3foPufMmYPp06fjmWee4TFRL6b93kePHo23335bP/ZpBNeuXUNUVBSAeyGqHQPla9XYlGykIKXl3ri+vr76shajv2hqamoQHR0NKaVF92mkU5m1twPVDB48WP/j3bFjB4QQGD58uNP+oM2PKTz++OM4cuQIJk+ejC+++MJhjzFnzhxMmzYNQgjMnTvX8K8xciwpJVJSUpCZmYnMzEyMGjVKdUlWaWtA+/bti8jISH0CERmTywPUfP2ntTcxW8dJjaK2ttZm51lVVWWY8ATadvyzNdpQ7tatWyGEwIgRIxwapMeOHdMXkD/++OMOuU9bnn76abz//vv44IMPMH/+fIaol9DCc/369UhOTlZdTptpXWifPn1Ul0I2KNvKT+tC3fFNzN/fHzU1NU0uq6qqQnBwsGGGb/Py8iCEsKsDtSYpKQlnzpxBdnY2hBA2h77a8/s8duwYJk6ciIkTJ0JKiS+//NIhtbbk6aefhpQSkydPZoh6OO2D3pgxY7B+/XqMHj1adUkOFxYWhvLyctVleC0lAap1oS0N5brjG1tgYKAhwlN77uLj41vcSqy9kpKSIKVEVlaW1eszMzORkpJi8btr6Xf56KOP4quvvnJYjW01b948TJ48GQsWLHDL1xq1buzYsRBCYN26dR4ZnqSesg60pa38Ghsb0blzZ8O9sUkp4efnZ9F9VldXG2avyfz8fCQkJDg8PM2NGDECp0+ftnpd8xA9efIkxo4da/V3OWHCBBw7dswpNbZVamoqQ9SDpaWlISUlRXUZ5KGUno2lpWUtRgvRuro6CCFsnsE9MDAQVVVVri3Kiri4OKcFZ1tlZmZizJgx+r/T09Mxbtw4hRVZN2/ePH3i0qJFiwzzWiNqC09d/+lOlJ9gzdr6T+3Y6J07d9C5c2dFlVny8/NDbW2txeUBAQGGCM/8/HwIIZCQkKAsDJKTk5GRkaHkse01f/58TJgwAYsWLVJdCrkAPyiRoygPUE1LL2rVL/i6ujr4+/tbva66utowZ3iPi4tDXl6ePoyrmurfW3ssXLgQu3btUl0GucDo0aNx6tQp1WWQBzBEgGpdaEtDuar16NHDovvUtvIzgoKCAsTHx6Nfv34wmUxKh3FHjx6NdevWNRnGdVfma1TNLyP3MHbsWLcbESH3oTxAhRCQUuJf//qXRYh26tQJd+/eVVjdPT169EBdXV2Ty7SdiIywlZ+UEjExMXr3qQ3jqpSSkuL2b1zbt2/X16guW7YMALBlyxasXLlScWVEZASG2rFA60TNZ+d26tRJP7WNis3N6+vr0adPH4sADQgIgMlkUr7hemFhIWJjY/V/x8XFGaIuAMjIyMDYsWNVl9Fhzz33HLZt2wYAWLFiheJqqK1OnjyJRx55RHUZ5MGUd6Aa8/1wmw+RNTQ0KJuR2717d4vwBFreC9eVYmJiYDKZcOXKFQDAlStXlHefnmTx4sXYunWr6jKIbAoLC8ONGzdUl+GVDBOgwL0Q1YZym1OxrKW+vh5+fn4Wl2t74TZfD6qC1oHGxsZCSom8vDzVJXmUHTt2YNmyZfrrjht8E5HGUAFqrvmxUG1ZS5cuXVzy+PX19QgPD0d9fX2Ty2traw0TnsC9DrSwsBDAvWUskydPVhaiycnJ+Prrr/V/axsqSCmRlpampKaOWLJkiX7GjmXLluHdd9+FEAIrV65kiLoxI28m317l5eVcC6qQ4QJU60JVz7zt0aOHRXgCsLoTkVH069cP+fn5qsvwOEuXLsW2bduwfPlySCkxZMgQrFq1SnVZRKSY4QLUXPNP+apn5dbW1trciYi8A2fhup8xY8Y0GRkhchTDBqhR1n8SNbd8+XJs2rRJdRlEpJghA9TX11fvNI0yaaOurs4Q3aet58Ioz1NzRq2rI959910O4bo5T3tNkhqGDFDg3nDtnTt3IITQZ9866gtAu25fV1eHiIgISCmt7oXrKkVFRYiOjra4vLCwEEIIxMfHu76oFmRkZEAI4RFrQTUrVqyAlBKbN29WXQq1wcmTJ62eyiw5OdmjtvPr3bs3l7IoYNgABX465tnY2KjvCNPRr65du+KHH35o1/fY2gfX1SIjI3H16lXVZbRZSkqKW86+Jc+Snp7O84GSUxg6QM2ZD+t2xJ07d9CtW7c237579+5Ku05ztjpQd8AhM1LF0ycRlZeXIzQ0VHUZXsnwAaqtAW1oaND/35Vf5ktZjBICRqmjrYx6PlAioo4wfIAagZ+fH65fv46AgADl4dW8C22+F67RPPLIIxzGJSKPZKjN5I1Om4mrakg3MjLSYqP4mJgYFBQUYOLEidzGz8FUncCAHCs9Pd3jf4/l5eUe/zMaETvQNjLCDkQtHQMtLCw03Czc5lR37+2xY8cOPPfcc6rLIAfw9GOgAGfhqsIAbQd/f3/U1tYaMgi084Ea1cmTJzF+/HjVZbTJjh07kJ6eju3bt6suhRwgIyPD5lKWrKwsBRWRp2CAtlNtba0hTmPWnJE70EceeQR//etfVZfRJjt37kR6ejp27NihuhQiC564MYk7Y4C6kcjISFy7ds3i8piYGEgpuZF8B+3atQvPPvus6jKIrJJSok+fPhBCoKysTHU5BE4iajd/f3/9WCgnmXiehQsXsvv0AqdOnXKrU5pp4VlWVobS0lKEhYU1uZ7HP9VgB2qnmpoaBAYGcjiFiJxKSomIiAiUlZWhpKTEIjxJHQZoB9TW1iIoKIghSmRw7vg3qh3vjIiIQGlpKUpKShAeHm71NqQGA9ROAQEBqK6uRk1NDYKCglSXY3hjx4419ESiXbt24dixY9i5c6fqUsgJUlJS3GYpixaKkZGREEIgKysLUsom4andJiwsDEIIDuEqwmOgHRAQEICqqipD7wRkNEY9brxgwQIsWLBAdRnkQkY9G0tUVBSKi4tRVFSEvn37Wr1NeHg4ysvLAQBlZWXo1auXK0ukH7ED7aDAwEBUV1erLsMt/PWvfzXkWtA9e/ZACIFFixapLoW8mNZVFhUVQUppMzy1D6GlpaWQUqJ3794urpQ0DFAH4bEI97ZgwQLs2rVLdRnkhbT3jujoaAghUFRU1OLt+/Tpg+zsbE4mMgAGqANUV1dDCIHg4GDVpbgFI33Q2LNnD44cOcLw9BJGeu0B9+qJiYmBEAJpaWn6sU9rt9NYW8ZCajBAHSAwMBCVlZUAjPcHajRpaWmYMGGC6jIAAKmpqTzu6eHMR4ZSUlIghEBmZqZh/k5jY2Nx4sQJSCkRFRVlcX3zmbhkLAxQB6qurkZISIjqMogI98Jn7NixEEJg/fr1kFLqmyckJyfj1KlTyoJUC8bCwkKbJ4jQjoNqM3GbL2Eh9RigDqKtB9U6UfqJlBJpaWlNJhA1P3G5KvPmzcOePXuUPT45nvZ6Gjt2LNLT05Genq5vJp+ZmYnk5GQA90JUCIHTp0+77HWoPUZcXByEECgsLLR528jISJSUlOD69evo06eP02uj9mOAklOdPHkSQgj87ne/g5QSJ06cwIkTJyCE0L8ee+wxi0A1f0Nz1hvb3LlzvTo8bT3f7kxKiXHjxiEtLQ0nT56ElBIpKSkWt9O6TyklRowYgZEjR0IIgTNnzuj34+i6pJSIj49HQUEBCgoK9OOfzW+nKS4u1rfwI2NigJLTjRkzBmlpaQCAcePG6W8mR48eBQAcPXq0SaBqX1OmTMHhw4fxi1/8okmYOiJgU1NTMX/+fI8IDXtIKbF69WqL5/zdd99VXZrdpJQYP348/uu//gtjx45t1/eePn0aSUlJGDFiBLKzszF8+HCcPXvWYXUlJCRACIErV660eLuoqKhWZ+GScTBAyWkyMjKwdu1anDx50uZtHn30Uaud0OHDh/GXv/wFTzzxBA4fPoypU6fi0KFDTd7sn3rqKRw8eBDTp0+32cG21Fnt3bvXaycRvfDCC9i8eTPeeecd/Tlavnw5VqxY4XYhqtU/fvx4/YOaPc6cOQMpJZKSkizuuyO19e/fH/n5+cjLy4OU0mLjFfNlLOnp6VZn4ZIxcSciFzHqDjyqHD9+HBMnTsSjjz5q9frJkydbfePSLvvss88wbdo0/OlPfwIACGH7s+CcOXPwwQcfAAB8fHzw/vvvY/78+U3u0xt/N++88w5WrVql/3vLli1u2ZFPnDgRx48fx4kTJzBu3DiH3Gd2djaGDh2Kc+fOAQDOnTuHwYMHt/t++vfvj7y8POTm5qJfv35WbxMTE4Nr167h6tWrDE83ww7UScw/ud66dQuhoaEWl3sqKSUyMjLw6quvWnSfUkocP34cEyZMwKOPPopjx47Z9Rj/9m//1mLH+dFHHwEAfvnLX2L69OkQQuCZZ57BBx98gLlz5+rHP7WlLJ7+OzHnCT9r87+jY8eOOSw8NWfPnoWUEoMHD8aQIUOQk5OjP7b5f1tz+fJli5PdN6//6tWrVpexkMG1NvRl/pWUlCSpdRUVFRKADA4ObnL5jRs3JAAZGhqqqDLny8jIkADk6NGjLa47ceKEBCDHjx/v8ro+/PBD+atf/crqdbt375YLFiyQJpPJxVWpsXr1arlhwwbVZdjFZDJJk8kkJ06cKAHIo0ePuryGQYMGyfPnz8uHHnpI/v3vf7frPmJiYiQAWVBQ4ODqyNF+zD2rmcgO1EmCgoJQUVHR5LLQ0FD9rAnSA7qA5jIzM5GSkoLk5GRkZGRYvc3YsWNx/PhxF1f2EymtjwDs3r2be+G6gccffxxCCBw9ehRffvmlkk05zp8/j0GDBuG7777D7NmzceHChTb/PWu3szULl9wLA9QJgoODLcLT3M2bNz12K67k5GSrp41KS0vDf/zHfyg7pdmcOXMwbdo0CCEwd+7cJtdps3G96VRmL7zwAjZt2mRxuZE/2Gm1HTlyBFJK/PznP1dc0T0DBgyAEAIXL15s8XbSbBkLeQYGqBNUVlZ63Y5Ep06dwpo1a6yGp1HelJ9++mlIKfH+++9b1LRr1y4sWrTIMLWqIKVscRau+dCVK2vSHm/SpEl49dVX8dhjj7ns8Vvz3Xff6TXOmDFDD9HmQ30AEB8f3+IyFnJDtsZ2rX3xGGjbVFRUyKCgIKvXacdBe/Xq5eKqnCczM1M+/PDDVq9LS0uTY8aMcXFFLdu7d6+cO3euxTHPnTt3yoULF3rFsdDVq1dLAPKdd96RUt47trh8+XK5ZcsWm9+zcOFCCUACkDt37tSPRzrT5MmTJQB5+PBhpz6OoyUkJOjPFQCZm5uruiSyE4+BktNkZWXhN7/5jdWTE7dlHagqe/fubbKURbNr1y4sWbJEQUWutXHjRjz//PP6v1euXIkhQ4Zg+fLlNr9n586d+hvHsWPH9PW4qampDu9KpVnndvjwYUyePNmh9+9sly9f1odsrc3CJQ9hK1mtfbEDbRutA7X26fzGjRseMwv3m2++kQBsdp/u2Mm999578tlnn3XL2lWYO3eu3mXt3bvXIV2pyWSSU6ZMkQDk559/7qBK1YiPj5eXL19WXQZ1ADtQBaqqqtCzZ08AP31IuXnzJnr16qW4Msc4ffo0Hn74YYwYMcKi+5Q/rgMdM2aMouraTlrpnN577z0sWbLEq4+HtpXWfT799NOYO3eu3pXu27fP6nHAlmi3mTp1Kg4fPozPP/8cU6ZMcfaPQGQ/W8lq7YsdaPvdunVL/4Tes2dP1eU4RFZWlhw+fLjV61paB2o0e/bskfPmzbPomLZv3y4ByMWLFyuqzDP88pe/bHIccP/+/S12p1OnTpWfffaZCyskal1LHSi38nOykJAQj+pkzpw5g5EjR2L48OEW17VlHajRpKamAkCTs7IsXrwYANzmZ2gLKV2/XaG2GxRwb0eoWbNmAQAOHDiA6dOnw8fHp0ldn332mUvrI+ooDuFSuwwfPhxSSpw+fdrq9bbWgRrRvHnzsHv3bgCWQ7mLFy/G9u3bPeLDj5QSL730EjZs2KCshj/+8Y/6Uo+ZM2dCCIGDBw/iqaeewqeffqqsLmeTbRy+JvfEACWHaGkdqNGlpqZaXQO6fft2PPfcc4qqcpw1a9bg//7v/1SXAeBe96mFys6dO/WTAXiq/v37QwiBvLw81aWQE3AI18FUDJWpdurUKSQnJ2PUqFGqS2k3bSmLdlqzXbt2WdzGnX+nUkq89dZbeOutt1SXQuRx2IE6UFVVldftQAQAo0aNgpQSmZmZqkuxy/z5861u47dkyRKMHj0ay5Ytc8thOCkl1qxZw/BUKDc3l2tAPRg7ULKqeWC4awfWVgsXLsTChQutdpt/+MMfAABbt251q+fh5ZdfRmRkJF566SXVpRB5JHagDlJVVYXg4GDVZThETk6Ovp5PCIFhw4apLskldu3ahWeffbbJZUuWLMHWrVvxhz/8AStWrFBUWfu5Y8dM5G4YoA5QXV2N4OBgBAYGorKyUnU5HXL+/Hn9BNNSSvztb3/Tr/OWN+XmMyeXLl2KrVu36tcZnZQSL7/8Mv73f/9XdSlEHo0B6iCBgYGoqqpSXUaHnD9/HoMHD25y2dChQ3H27FlkZ2dbXfvpSRYuXIjx48dDCGGxH+7SpUsxbNgwrFy5UlF1bSOlxCuvvILw8HB9+QoROQePgTpAQECA24enZtCgQcjJyVFdhjKLFi2CyWRCenq6282+1cKzd+/e+Pd//3fV5RB5PHagHVRdXY2goCDVZZCDvffeexZrQJcvX44tW7YYdhj3tddew5tvvqm6DLIiISEB+fn5qssgB2OAdoBR30g7ylN/rrbSdiGyZsuWLVi5cqXhniOtnv/5n//Byy+/rLgaIu/AALVTTU0NhBCIjY1FdXW16nIc5ttvv8WQIUNUl6Gcra38VqxYgSFDhmDVqlWKKrMkpcRvf/tbhISEMDwNKDc3F/369VNdBjkBA7QD/P39PSo8qanWtvIzQheqhee6detUl0LkdRigdqipqUFgYKDqMhwuMTFRn0Bkfsqes2fPYtmyZcjOzlZcoRrWutCBAwdi1apVykN07dq1WLduHd544w28+uqrSmsh8jYMUDv5+/ujpqZGdRkOl5iYiN27d3vlRgrNtbSV3/PPP4+BAwdi9erViqr7KdjfeOMNvPbaa8rqIPJWDNB2qq2t9cju09zgwYMtThzrrd0ncG8rv5b2w1XRhUopsXbtWrzxxhsuf2wiuofrQNvJz89P+bAduc6SJUtgMpmwbNkyCCGwZcsW/UTQK1euxObNm7F69Wps2rTJpa+L3/3udzZfi+62ftVbxMfHIy8vjxOKPAgDtB1qa2sRGRmJ2tpa1aWQCy1duhQAsGzZMvj4+GDIkCFNdiR6/vnnsXHjRrzwwgsureu///u/rV7+yiuvICwsjJspEDkZA5SoDZYuXQqTyaRvKK91n+Z+/etfu7QmjoQQqcVjoG1UV1eHgIAA1WWQASxfvtwiPFVYu3YtXn/9dYvL169fj9LSUu5KZCB5eXmIi4tTXQY5GAO0Derq6uDv7w8/Pz8O33o5bTs/I3j99dfx29/+1mon+uabb6K0tJQn0yZyIgZoK+rr6+Hv748ePXowPMlw1q5dCyEEfv/731tc9+abb+I3v/mN64si8hIM0Fb06NEDUkrU1dWpLoUU2rZtmyFPqP36669DSmlzE4U1a9awCyVyEgYoURstW7bMMMO3zbW0nd+aNWvw9ttvu7YgIi/AACVqxbZt25CVlYV3331XdSk2/f73v8crr7xicTz0rbfegpQSV69exYYNGxRVR8C9iUSTJ09GQUGB6lLIQRigRC3Yvn07srKysG3bNtWltOq1116DEALr16+3ev2LL77IEFUoPj4eV65cUV0GORDXgRLZoJ2NpaUzshjJunXrYDKZrF739ttv27yOiOzDDpSoBYsXL3aL7lOzfv16lJeXW10DumHDBpdv9kA/yc/Ph5QSsbGxqkshB2GAEnmgl19+2WqIvvjii9i4cSN3MSJyAAYokRU7duzA119/je3bt6supd3Wr18PKaXVjRS0LvSFF17Apk2bFFVI5BkYoETN7NixA0uWLFFdBhEZHAOUyIpnn33WLbtPc2+++SaKioqsbqSwceNGXLhwgV0oUQcwQInM7Ny50+O6T26kQOQcXMZC9KNdu3bhxIkTHjXBRus+X3rpJQghmpyzdNOmTVi1ahU2b96M559/3iX1eNJzS8QOlMjDabsR5efnW91IYdWqVU7folBKCSklZs2aBSEEhBBYtGgRpJR48sknnfrYRM7CDpToRwsXLsTChQtVl+FSmzZtgpQSK1euBACHbphv3m3Onj0b+/fvBwAcOHAAM2bMcNjjEKnCACXyEhs2bNA7QR8fH/3yzZs3d3iXouZDsz4+PpgzZw7++Mc/6pft378fM2fO7NDjEBkJh3CJvMiLL74IIQQ2btzY5PItW7a0u/vUwlhKiblz5+pDs0II7Nu3Dx999FGT2zA8ydOwAyXyIloX2hHa9y9YsACpqan65Xv37sUzzzzTofsmcifsQIm8UHt3IjLvJBctWgQhBFJTU7Fnzx79coYneRsGKJGX0fbCbctGClo4LlmyRB+enTBhgn75vHnzXFQ1kfFwCJe8RvPJM9plACwu90bmQ7va8/Hcc89hx44dAID33nsPixYtUlEakSGxAyWvsG/fPoshxtTUVAghsGDBAkVVqbVp0yZcuHABmzdv1peyaF2mdgq37du3Nxm6JaKfsAMlrzVv3jxIKXHkyBHVpSi1atUqrFq1CsC92bjLly9XXBGRe2AHSl7FfDJMamqq13afGm0jBe2L4UnUduxAyWt8+OGH+PDDD1WXQUQegh0oeY1f/epXTbqtPXv2qC6JiNwYA5S82rx587B7927VZRCRG+IQLnmFOXPmYPbs2RaXazvpsBslovZiB0pewdoyFiKijvBpz76YPj4+twBcc145REREhhIlpexp7Yp2BSgRERHdwyFcIiIiOzBAiYiI7MAAJSIisgMDlIiIyA4MUCIiIjswQImIiOzAACUiIrIDA5SIiMgODFAiIiI7/D9aZlIR2307fgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 5.0\n",
      "LD for BEAM SEARCH- 4.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C20H17F2N5O2/c21-15-6-3-5-13(10-15)18-19(28)23-8-9-27(18)20(29)17-12-26(25-24-17)11-14-4-1-2-7-16(14)22/h1-7,10,12,18H,8-9,11H2,(H,23,28)/t18-/m1/s1\n",
      "\n",
      "\n",
      "PREDICTED-- C20H17F2N5O2/c21-15-6-3-5-13(10-15)18-19(28)23-8-9-27(18)20(29)17-12-26(25-24-17)11-13-4-1-2-7-16(14)22/h1-7,10,12,18H,8-9,11H2,(H,23,28)/t18-/m0/s1\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 20H17F2N5O2/c21-15-6-3-5-14(10-15)18-19(28)23-8-9-27(18)20(29)17-12-26(25-24-17)11-13-4-1-2-7-16(14)22/h1-7,10,12,18H,8-9,11H2,(H,23,28)/t18-/m0/s1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 2.0\n",
      "LD for BEAM SEARCH- 3.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C27H29NO5/c1-19-16-24(25(29)22-11-13-23(32-4)14-12-22)28(17-19)15-5-6-20-7-9-21(10-8-20)18-33-27(2,3)26(30)31/h5-14,16-17H,15,18H2,1-4H3,(H,30,31)/b6-5+\n",
      "\n",
      "\n",
      "PREDICTED-- C27H29NO5/c1-19-16-24(24(29)22-11-13-23(32-4)14-12-22)28(17-20)15-5-6-20-7-9-21(10-8-20)18-33-27(2,3)26(30)31/h5-14,16-17H,15,18H2,1-4H3,(H,30,31)/b6-4+\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 27H29NO5/c1-19-16-24(24(29)22-11-13-23(32-4)14-12-22)28(17-20)15-5-6-20-7-9-21(10-8-20)18-33-27(2,3)26(30)31/h5-14,16-17H,15,18H2,1-4H3,(H,30,31)/b5-4+\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 4.0\n",
      "LD for BEAM SEARCH- 5.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C15H30N2/c1-3-13(2)17-11-7-10-16-15(12-17)14-8-5-4-6-9-14/h13-16H,3-12H2,1-2H3\n",
      "\n",
      "\n",
      "PREDICTED-- C15H30N2/c1-3-13(2)17-11-7-10-16-15(12-17)14-8-5-4-6-9-14/h13-16H,3-12H2,1-2H3\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 15H30N2/c1-3-13(2)17-11-6-10-16-15(12-17)14-8-5-4-6-9-14/h13-16H,3-12H2,1-2H3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C30H35Cl2N3O5S/c1-6-25(29(37)33-30(2,3)4)34(19-21-15-17-22(40-5)18-16-21)27(36)20-35(26-14-10-13-24(31)28(26)32)41(38,39)23-11-8-7-9-12-23/h7-18,25H,6,19-20H2,1-5H3,(H,33,37)/t25-/m1/s1\n",
      "\n",
      "\n",
      "PREDICTED-- C30H35Cl2N3O5S/c1-6-25(29(37)33-30(2,3)4)34(19-21-15-17-22(39-5)18-16-21)27(36)20-35(24-13-10-13-24(31)28(26)32)41(38,39)24-12-8-7-9-13-24/h7-18,25H,6,10-20H2,1-5H3,(H,33,37)/t25-/m0/s1\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 30H35Cl2N3O5S/c1-6-25(29(37)33-30(2,3)4)34(19-21-15-17-22(49-5)18-16-21)27(36)20-35(24-13-10-13-24(31)28(26)32)41(38,39)24-12-8-7-9-13-24/h7-18,25H,6,10-20H2,1-5H3,(H,33,37)/t25-/m0/s1\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 10.0\n",
      "LD for BEAM SEARCH- 9.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C27H26Cl2N2O6S/c1-18-2-7-22(8-3-18)38(35,36)31-12-10-30(11-13-31)27(34)23-14-19(15-26(32)33)4-9-25(23)37-17-20-5-6-21(28)16-24(20)29/h2-9,14,16H,10-13,15,17H2,1H3,(H,32,33)\n",
      "\n",
      "\n",
      "PREDICTED-- C27H26Cl2N2O6S/c1-18-2-7-22(8-3-18)38(35,36)31-12-10-30(11-13-31)27(34)23-14-19(16-26(32)33)4-9-25(23)37-17-20-4-6-21(28)16-24(20)29/h2-9,14-15H,10-13,16-17H2,1H3,(H,32,33)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 27H26Cl2N2O6S/c1-18-2-7-22(8-3-18)38(35,36)31-12-10-30(11-13-31)27(34)23-14-19(16-26(32)33)4-9-25(23)37-17-20-5-6-21(28)16-24(20)29/h2-9,14-15H,10-13,16-17H2,1H3,(H,32,33)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 6.0\n",
      "LD for BEAM SEARCH- 5.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C13H17ClN2/c1-9-6-7-11(14)8-12(9)16-13(15)10-4-2-3-5-10/h6-8,10H,2-5H2,1H3,(H2,15,16)\n",
      "\n",
      "\n",
      "PREDICTED-- C13H17ClN2/c1-9-6-7-11(14)8-12(9)16-13(15)10-4-2-3-5-10/h6-8,10H,2-5H2,1H3,(H2,15,16)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 13H17ClN2/c1-9-6-7-11(14)8-12(9)16-13(15)10-4-2-3-5-10/h6-8,10H,2-5H2,1H3,(H3,15,16)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C32H22Cl2N4O5/c1-41-26-12-7-13-27-22(26)16-28(43-27)31-37-25-11-6-5-10-21(25)32(40)38(31)35-17-19-14-23(33)30(24(34)15-19)42-18-29(39)36-20-8-3-2-4-9-20/h2-17H,18H2,1H3,(H,36,39)\n",
      "\n",
      "\n",
      "PREDICTED-- C32H22Cl2N4O5/c1-42-26-12-7-11-25-24(26)19-39(44-27)31-36-25-11-6-6-12-27(25)38(31)33(30)39)17-19-14-23(33)29(24(33)14-19)41-18-29(39)36-20-8-3-2-4-9-20/h2-17H,18H2,1H3,(H,36,39)\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 32H22Cl2N4O5/c1-42-26-12-7-11-25-24(26)19-39(44-27)31-36-25-11-6-6-12-27(25)38(33)33(30)39)17-19-14-23(33)29(24(33)14-19)41-18-29(39)36-20-8-3-2-4-9-20/h2-17H,18H2,1H3,(H,36,39)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 24.0\n",
      "LD for BEAM SEARCH- 24.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C23H14BrNO3/c24-15-8-6-7-14(13-15)20-19-21(26)17-11-4-5-12-18(17)28-22(19)23(27)25(20)16-9-2-1-3-10-16/h1-13,20H\n",
      "\n",
      "\n",
      "PREDICTED-- C23H14BrNO3/c24-15-8-6-7-14(13-15)19-19-21(26)17-11-4-5-12-18(17)28-22(19)23(27)25(20)16-9-2-1-3-10-16/h1-13,20H\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 23H14BrNO3/c24-15-8-6-7-14(13-15)19-18-21(26)17-11-4-5-12-18(17)28-22(19)23(27)25(20)16-9-2-1-3-10-16/h1-13,20H\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 2.0\n",
      "LD for BEAM SEARCH- 3.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C6H8Cl2O2/c1-3-10-6(8)4(2)5(7)9/h3H2,1-2H3/b6-4-\n",
      "\n",
      "\n",
      "PREDICTED-- C6H8Cl2O2/c1-3-10-6(8)4(2)5(8)9/h4H,3H2,1-2H3/<pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad>\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 6H8Cl2O2/c1-3-10-5(8)4(2)5(8)9/h4H,3H2,1-2H3/<pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad><pad>\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 9.0\n",
      "LD for BEAM SEARCH- 10.0\n",
      "***********************************************\n",
      "\n",
      "LABEL-- C17H23FN4O2/c1-12(2)16-19-17(20-24-16)22-9-7-21(8-10-22)11-13-5-4-6-14(23-3)15(13)18/h4-6,12H,7-11H2,1-3H3\n",
      "\n",
      "\n",
      "PREDICTED-- C17H23FN4O2/c1-12(2)16-19-17(20-24-16)22-9-7-21(8-10-22)11-13-5-4-6-14(23-3)15(13)18/h4-6,12H,7-11H2,1-3H3\n",
      "\n",
      "\n",
      "BEAM SEARCH-- 17H23FN4O2/c1-12(2)16-19-17(21-24-16)22-9-7-21(8-10-22)11-13-5-4-6-14(23-3)15(13)18/h4-6,12H,7-11H2,1-3H3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LD for PREDICTED- 0.0\n",
      "LD for BEAM SEARCH- 1.0\n",
      "***********************************************\n",
      "\n"
     ]
    }
   ],
   "source": [
    "predictions_seq, predictions_prob= get_pred(imgs)\n",
    "for i in range(BATCH_SIZE):\n",
    "    show(imgs[i], convert(lbls[i].numpy()),convert(predictions_seq[i].numpy()),\n",
    "                     convert(beam_search_decoder(predictions_prob[i], 4)[1][0]))\n",
    "    print('LD for PREDICTED-', get_levenshtein_distance(predictions_seq[i][tf.newaxis, ],\n",
    "                                    lbls[i][tf.newaxis, ]).numpy())\n",
    "    print('LD for BEAM SEARCH-', get_levenshtein_distance(np.array([beam_search_decoder(predictions_prob[i], 4)[1][0]]),\n",
    "                                    lbls[i][tf.newaxis, 1:]).numpy())\n",
    "    print('***********************************************\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "annoying-input",
   "metadata": {
    "papermill": {
     "duration": 0.079573,
     "end_time": "2021-05-05T14:21:55.930357",
     "exception": false,
     "start_time": "2021-05-05T14:21:55.850784",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "hairy-monster",
   "metadata": {
    "papermill": {
     "duration": 0.081084,
     "end_time": "2021-05-05T14:21:56.092753",
     "exception": false,
     "start_time": "2021-05-05T14:21:56.011669",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "medium-newton",
   "metadata": {
    "papermill": {
     "duration": 0.078537,
     "end_time": "2021-05-05T14:21:56.250656",
     "exception": false,
     "start_time": "2021-05-05T14:21:56.172119",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "saving-runner",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-05T14:21:56.413373Z",
     "iopub.status.busy": "2021-05-05T14:21:56.412769Z",
     "iopub.status.idle": "2021-05-05T14:21:56.416464Z",
     "shell.execute_reply": "2021-05-05T14:21:56.415943Z"
    },
    "papermill": {
     "duration": 0.086625,
     "end_time": "2021-05-05T14:21:56.416635",
     "exception": false,
     "start_time": "2021-05-05T14:21:56.330010",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#(20, 199, 41)\n",
    "#tf.reshape(predictions_prob, (predictions_prob.shape[0], (MAX_INCHI_LEN-1), VOCAB_SIZE))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "virgin-rehabilitation",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-05T14:21:56.578872Z",
     "iopub.status.busy": "2021-05-05T14:21:56.578100Z",
     "iopub.status.idle": "2021-05-05T14:21:56.580846Z",
     "shell.execute_reply": "2021-05-05T14:21:56.580170Z"
    },
    "papermill": {
     "duration": 0.085725,
     "end_time": "2021-05-05T14:21:56.580981",
     "exception": false,
     "start_time": "2021-05-05T14:21:56.495256",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# i= 18\n",
    "# result = beam_search_decoder(predictions_prob[i], 6)\n",
    "# # print result\n",
    "# for seq in result:\n",
    "#     f = convert(seq[0])\n",
    "#     print('C'+ f)\n",
    "#     print(convert(predictions_seq.numpy()[i])[1:]==f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "straight-blast",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-05T14:21:56.742242Z",
     "iopub.status.busy": "2021-05-05T14:21:56.741652Z",
     "iopub.status.idle": "2021-05-05T14:21:56.744168Z",
     "shell.execute_reply": "2021-05-05T14:21:56.744697Z"
    },
    "papermill": {
     "duration": 0.08588,
     "end_time": "2021-05-05T14:21:56.744886",
     "exception": false,
     "start_time": "2021-05-05T14:21:56.659006",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# predictions_seq, predictions_prob= get_pred(imgs)\n",
    "# for i in range(BATCH_SIZE):\n",
    "#     show(imgs[i], convert(lbls[i].numpy()),convert(predictions_seq[i].numpy()),\n",
    "#                      convert(beam_search_decoder(predictions_prob[i], 2)[1][0]))\n",
    "#     print('***********************************************\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "scenic-dairy",
   "metadata": {
    "papermill": {
     "duration": 0.079515,
     "end_time": "2021-05-05T14:21:56.903454",
     "exception": false,
     "start_time": "2021-05-05T14:21:56.823939",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 292.213379,
   "end_time": "2021-05-05T14:21:58.196398",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2021-05-05T14:17:05.983019",
   "version": "2.3.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}