diff --git a/README.md b/README.md
index 652abe1..a5775af 100644
--- a/README.md
+++ b/README.md
@@ -5,7 +5,7 @@
-
+
---
@@ -167,6 +167,7 @@ Accuracy based on arc, types and root accuracies after 15 epochs only.
5. Bidirectional RNN + Biaffine Attention + Cross Entropy, arc accuracy 72.42%, types accuracy 63.53%, root accuracy 68.51%
6. BERT Base + Biaffine Attention + Cross Entropy, arc accuracy 72.85%, types accuracy 67.11%, root accuracy 73.93%
7. Bidirectional RNN + Stackpointer, arc accuracy 61.88%, types accuracy 48.20%, root accuracy 89.39%
+8. XLNET Base + Biaffine Attention + Cross Entropy, arc accuracy 74.41%, types accuracy 71.37%, root accuracy 73.17%
### [Entity-Tagging](entity-tagging)
diff --git a/dependency-parser/8.xlnet-biaffine-attention-cross-entropy.ipynb b/dependency-parser/8.xlnet-biaffine-attention-cross-entropy.ipynb
new file mode 100644
index 0000000..dc02b25
--- /dev/null
+++ b/dependency-parser/8.xlnet-biaffine-attention-cross-entropy.ipynb
@@ -0,0 +1,1608 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# !wget https://raw.githubusercontent.com/UniversalDependencies/UD_English-EWT/master/en_ewt-ud-dev.conllu\n",
+ "# !wget https://raw.githubusercontent.com/UniversalDependencies/UD_English-EWT/master/en_ewt-ud-train.conllu\n",
+ "# !wget https://raw.githubusercontent.com/UniversalDependencies/UD_English-EWT/master/en_ewt-ud-test.conllu\n",
+ "# !wget https://storage.googleapis.com/xlnet/released_models/cased_L-12_H-768_A-12.zip -O xlnet.zip\n",
+ "# !unzip xlnet.zip"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "os.environ['CUDA_VISIBLE_DEVICES'] = '1'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "tag2idx = {'PAD': 0, 'X': 1}\n",
+ "tag_idx = 2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import sentencepiece as spm\n",
+ "from prepro_utils import preprocess_text, encode_ids\n",
+ "\n",
+ "sp_model = spm.SentencePieceProcessor()\n",
+ "sp_model.Load('xlnet_cased_L-12_H-768_A-12/spiece.model')\n",
+ "\n",
+ "def tokenize_fn(text):\n",
+ " text = preprocess_text(text, lower= False)\n",
+ " return encode_ids(sp_model, text)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "SEG_ID_A = 0\n",
+ "SEG_ID_B = 1\n",
+ "SEG_ID_CLS = 2\n",
+ "SEG_ID_SEP = 3\n",
+ "SEG_ID_PAD = 4\n",
+ "\n",
+ "special_symbols = {\n",
+ " \"\" : 0,\n",
+ " \"\" : 1,\n",
+ " \"\" : 2,\n",
+ " \"\" : 3,\n",
+ " \"\" : 4,\n",
+ " \"\" : 5,\n",
+ " \"\" : 6,\n",
+ " \"\" : 7,\n",
+ " \"\" : 8,\n",
+ "}\n",
+ "\n",
+ "VOCAB_SIZE = 32000\n",
+ "UNK_ID = special_symbols[\"\"]\n",
+ "CLS_ID = special_symbols[\"\"]\n",
+ "SEP_ID = special_symbols[\"\"]\n",
+ "MASK_ID = special_symbols[\"\"]\n",
+ "EOD_ID = special_symbols[\"\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def process_corpus(corpus, until = None):\n",
+ " global word2idx, tag2idx, char2idx, word_idx, tag_idx, char_idx\n",
+ " sentences, words, depends, labels, pos, sequences = [], [], [], [], [], []\n",
+ " temp_sentence, temp_word, temp_depend, temp_label, temp_pos = [], [], [], [], []\n",
+ " segments, masks = [], []\n",
+ " first_time = True\n",
+ " for sentence in corpus:\n",
+ " try:\n",
+ " if len(sentence):\n",
+ " if sentence[0] == '#':\n",
+ " continue\n",
+ " if first_time:\n",
+ " print(sentence)\n",
+ " first_time = False\n",
+ " sentence = sentence.split('\\t')\n",
+ " if sentence[7] not in tag2idx:\n",
+ " tag2idx[sentence[7]] = tag_idx\n",
+ " tag_idx += 1\n",
+ " temp_word.append(sentence[1])\n",
+ " temp_depend.append(int(sentence[6]) + 1)\n",
+ " temp_label.append(tag2idx[sentence[7]])\n",
+ " temp_sentence.append(sentence[1])\n",
+ " temp_pos.append(sentence[3])\n",
+ " else:\n",
+ " if len(temp_sentence) < 2 or len(temp_word) != len(temp_label):\n",
+ " temp_word = []\n",
+ " temp_depend = []\n",
+ " temp_label = []\n",
+ " temp_sentence = []\n",
+ " temp_pos = []\n",
+ " continue\n",
+ " bert_tokens = []\n",
+ " labels_ = []\n",
+ " depends_ = []\n",
+ " seq_ = []\n",
+ " for no, orig_token in enumerate(temp_word):\n",
+ " t = tokenize_fn(orig_token)\n",
+ " labels_.append(temp_label[no])\n",
+ " depends_.append(temp_depend[no])\n",
+ " bert_tokens.extend(t)\n",
+ " labels_.extend([1] * (len(t) - 1))\n",
+ " depends_.extend([0] * (len(t) - 1))\n",
+ " seq_.append(no + 1)\n",
+ " bert_tokens.extend([4, 3])\n",
+ " labels_.extend([0, 0])\n",
+ " depends_.extend([0, 0])\n",
+ " segment = [0] * (len(bert_tokens) - 1) + [SEG_ID_CLS]\n",
+ " input_mask = [0] * len(segment)\n",
+ " words.append(bert_tokens)\n",
+ " depends.append(depends_)\n",
+ " labels.append(labels_)\n",
+ " sentences.append(temp_sentence)\n",
+ " pos.append(temp_pos)\n",
+ " sequences.append(seq_)\n",
+ " segments.append(segment)\n",
+ " masks.append(input_mask)\n",
+ " temp_word = []\n",
+ " temp_depend = []\n",
+ " temp_label = []\n",
+ " temp_sentence = []\n",
+ " temp_pos = []\n",
+ " except Exception as e:\n",
+ " print(e, sentence)\n",
+ " return sentences[:-1], words[:-1], depends[:-1], labels[:-1], pos[:-1], sequences[:-1], segments[:-1], masks[:-1]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1\tFrom\tfrom\tADP\tIN\t_\t3\tcase\t3:case\t_\n",
+ "invalid literal for int() with base 10: '_' ['10.1', 'has', 'have', 'VERB', 'VBZ', '_', '_', '_', '8:parataxis', 'CopyOf=-1']\n",
+ "invalid literal for int() with base 10: '_' ['21.1', 'has', 'have', 'VERB', 'VBZ', '_', '_', '_', '16:conj:and', 'CopyOf=-1']\n"
+ ]
+ }
+ ],
+ "source": [
+ "with open('en_ewt-ud-dev.conllu') as fopen:\n",
+ " dev = fopen.read().split('\\n')\n",
+ "\n",
+ "sentences_dev, words_dev, depends_dev, labels_dev, _, seq_dev, segments_dev, masks_dev = process_corpus(dev)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1\tWhat\twhat\tPRON\tWP\tPronType=Int\t0\troot\t0:root\t_\n",
+ "invalid literal for int() with base 10: '_' ['24.1', 'left', 'left', 'VERB', 'VBN', 'Tense=Past|VerbForm=Part', '_', '_', '6:parataxis', 'CopyOf=6']\n"
+ ]
+ }
+ ],
+ "source": [
+ "with open('en_ewt-ud-test.conllu') as fopen:\n",
+ " test = fopen.read().split('\\n')\n",
+ "\n",
+ "sentences_test, words_test, depends_test, labels_test, _, seq_test, segments_test, masks_test = process_corpus(test)\n",
+ "sentences_test.extend(sentences_dev)\n",
+ "words_test.extend(words_dev)\n",
+ "depends_test.extend(depends_dev)\n",
+ "labels_test.extend(labels_dev)\n",
+ "seq_test.extend(seq_dev)\n",
+ "segments_test.extend(segments_dev)\n",
+ "masks_test.extend(masks_dev)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1\tAl\tAl\tPROPN\tNNP\tNumber=Sing\t0\troot\t0:root\tSpaceAfter=No\n",
+ "invalid literal for int() with base 10: '_' ['8.1', 'reported', 'report', 'VERB', 'VBN', 'Tense=Past|VerbForm=Part|Voice=Pass', '_', '_', '5:conj:and', 'CopyOf=5']\n",
+ "invalid literal for int() with base 10: '_' ['22.1', 'used', 'use', 'VERB', 'VBN', 'Tense=Past|VerbForm=Part', '_', '_', '13:advcl:with|17:conj:and', 'CopyOf=17']\n",
+ "invalid literal for int() with base 10: '_' ['22.1', 'used', 'use', 'VERB', 'VBN', 'Tense=Past|VerbForm=Part', '_', '_', '13:advcl:with|17:conj:and', 'CopyOf=17']\n",
+ "invalid literal for int() with base 10: '_' ['11.1', 'called', 'call', 'VERB', 'VBN', 'Tense=Past|VerbForm=Part|Voice=Pass', '_', '_', '3:conj:and', 'CopyOf=3']\n",
+ "invalid literal for int() with base 10: '_' ['14.1', 'is', 'be', 'VERB', 'VBZ', '_', '_', '_', '1:conj:and', 'CopyOf=1']\n",
+ "invalid literal for int() with base 10: '_' ['20.1', 'reflect', 'reflect', 'VERB', 'VBP', 'Mood=Ind|Tense=Pres|VerbForm=Fin', '_', '_', '7:acl:relcl|9:conj', 'CopyOf=9']\n",
+ "invalid literal for int() with base 10: '_' ['21.1', 'recruited', 'recruit', 'VERB', 'VBD', 'Mood=Ind|Tense=Past|VerbForm=Fin', '_', '_', '9:conj:and', 'CopyOf=9']\n",
+ "invalid literal for int() with base 10: '_' ['9.1', 'wish', 'wish', 'VERB', 'VBP', 'Mood=Ind|Tense=Pres|VerbForm=Fin', '_', '_', '2:conj:and', 'CopyOf=2']\n",
+ "invalid literal for int() with base 10: '_' ['38.1', 'supplied', 'supply', 'VERB', 'VBN', 'Tense=Past|VerbForm=Part|Voice=Pass', '_', '_', '16:conj:and', 'CopyOf=16']\n",
+ "invalid literal for int() with base 10: '_' ['18.1', 'keep', 'keep', 'VERB', 'VB', 'Mood=Imp|VerbForm=Fin', '_', '_', '14:conj:and', 'CopyOf=14']\n",
+ "invalid literal for int() with base 10: '_' ['21.1', 'keep', 'keep', 'VERB', 'VB', 'Mood=Imp|VerbForm=Fin', '_', '_', '14:conj:and', 'CopyOf=14']\n",
+ "invalid literal for int() with base 10: '_' ['18.1', 'mean', 'mean', 'VERB', 'VB', 'VerbForm=Inf', '_', '_', '8:conj', 'CopyOf=8']\n",
+ "invalid literal for int() with base 10: '_' ['30.1', 'play', 'play', 'VERB', 'VBP', 'Mood=Ind|Tense=Pres|VerbForm=Fin', '_', '_', '18:acl:relcl|27:conj:but', 'CopyOf=27']\n",
+ "invalid literal for int() with base 10: '_' ['22.1', 'have', 'have', 'VERB', 'VBP', 'Mood=Ind|Tense=Pres|VerbForm=Fin', '_', '_', '17:conj', 'CopyOf=17']\n",
+ "invalid literal for int() with base 10: '_' ['27.1', 'have', 'have', 'VERB', 'VBP', 'Mood=Ind|Tense=Pres|VerbForm=Fin', '_', '_', '17:conj', 'CopyOf=17']\n",
+ "invalid literal for int() with base 10: '_' ['49.1', 'helped', 'help', 'VERB', 'VBD', '_', '_', '_', '38:conj:but', 'CopyOf=38']\n",
+ "invalid literal for int() with base 10: '_' ['7.1', 'found', 'find', 'VERB', 'VBD', 'Mood=Ind|Tense=Past|VerbForm=Fin', '_', '_', '3:conj', 'CopyOf=3']\n",
+ "invalid literal for int() with base 10: '_' ['10.1', 'excited', 'excited', 'ADJ', 'JJ', 'Degree=Pos', '_', '_', '4:advcl', 'CopyOf=4']\n",
+ "invalid literal for int() with base 10: '_' ['15.1', \"'s\", 'be', 'VERB', 'VBZ', '_', '_', '_', '2:conj:and', 'CopyOf=2']\n",
+ "invalid literal for int() with base 10: '_' ['25.1', 'took', 'take', 'VERB', 'VBD', 'Mood=Ind|Tense=Past|VerbForm=Fin', '_', '_', '17:conj:and', 'CopyOf=17']\n",
+ "invalid literal for int() with base 10: '_' ['10.1', 'loss', 'lose', 'VERB', 'VBD', 'Mood=Ind|Tense=Past|VerbForm=Fin', '_', '_', '3:conj:and', 'CopyOf=3']\n",
+ "invalid literal for int() with base 10: '_' ['11.1', 'leave', 'leave', 'VERB', 'VB', 'VerbForm=Inf', '_', '_', '7:parataxis', 'CopyOf=7']\n",
+ "invalid literal for int() with base 10: '_' ['24.1', 'charge', 'charge', 'VERB', 'VBP', 'Mood=Ind|Tense=Pres|VerbForm=Fin', '_', '_', '16:conj:and', 'CopyOf=16']\n"
+ ]
+ }
+ ],
+ "source": [
+ "with open('en_ewt-ud-train.conllu') as fopen:\n",
+ " train = fopen.read().split('\\n')\n",
+ "\n",
+ "sentences_train, words_train, depends_train, labels_train, _, _, segments_train, masks_train = process_corpus(train)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(12000, 3824)"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(sentences_train), len(sentences_test)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "idx2tag = {v:k for k, v in tag2idx.items()}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "train_X = words_train\n",
+ "train_Y = labels_train\n",
+ "train_depends = depends_train\n",
+ "\n",
+ "test_X = words_test\n",
+ "test_Y = labels_test\n",
+ "test_depends = depends_test"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
+ "/usr/lib/python3/dist-packages/requests/__init__.py:80: RequestsDependencyWarning: urllib3 (1.25.6) or chardet (3.0.4) doesn't match a supported version!\n",
+ " RequestsDependencyWarning)\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "WARNING:tensorflow:From /home/husein/testing/model_utils.py:295: The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.\n",
+ "\n",
+ "WARNING:tensorflow:From /home/husein/testing/xlnet.py:70: The name tf.gfile.Open is deprecated. Please use tf.io.gfile.GFile instead.\n",
+ "\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
+ "/home/husein/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+ " np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
+ ]
+ }
+ ],
+ "source": [
+ "import xlnet\n",
+ "import model_utils\n",
+ "import tensorflow as tf\n",
+ "import numpy as np\n",
+ "\n",
+ "kwargs = dict(\n",
+ " is_training=True,\n",
+ " use_tpu=False,\n",
+ " use_bfloat16=False,\n",
+ " dropout=0.1,\n",
+ " dropatt=0.1,\n",
+ " init='normal',\n",
+ " init_range=0.1,\n",
+ " init_std=0.05,\n",
+ " clamp_len=-1)\n",
+ "\n",
+ "xlnet_parameters = xlnet.RunConfig(**kwargs)\n",
+ "xlnet_config = xlnet.XLNetConfig(json_path='xlnet_cased_L-12_H-768_A-12/xlnet_config.json')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "5625 562\n"
+ ]
+ }
+ ],
+ "source": [
+ "epoch = 15\n",
+ "batch_size = 32\n",
+ "warmup_proportion = 0.1\n",
+ "num_train_steps = int(len(train_X) / batch_size * epoch)\n",
+ "num_warmup_steps = int(num_train_steps * warmup_proportion)\n",
+ "print(num_train_steps, num_warmup_steps)\n",
+ "\n",
+ "training_parameters = dict(\n",
+ " decay_method = 'poly',\n",
+ " train_steps = num_train_steps,\n",
+ " learning_rate = 2e-5,\n",
+ " warmup_steps = num_warmup_steps,\n",
+ " min_lr_ratio = 0.0,\n",
+ " weight_decay = 0.00,\n",
+ " adam_epsilon = 1e-8,\n",
+ " num_core_per_host = 1,\n",
+ " lr_layer_decay_rate = 1,\n",
+ " use_tpu=False,\n",
+ " use_bfloat16=False,\n",
+ " dropout=0.0,\n",
+ " dropatt=0.0,\n",
+ " init='normal',\n",
+ " init_range=0.1,\n",
+ " init_std=0.02,\n",
+ " clip = 1.0,\n",
+ " clamp_len=-1,)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class Parameter:\n",
+ " def __init__(self, decay_method, warmup_steps, weight_decay, adam_epsilon, \n",
+ " num_core_per_host, lr_layer_decay_rate, use_tpu, learning_rate, train_steps,\n",
+ " min_lr_ratio, clip, **kwargs):\n",
+ " self.decay_method = decay_method\n",
+ " self.warmup_steps = warmup_steps\n",
+ " self.weight_decay = weight_decay\n",
+ " self.adam_epsilon = adam_epsilon\n",
+ " self.num_core_per_host = num_core_per_host\n",
+ " self.lr_layer_decay_rate = lr_layer_decay_rate\n",
+ " self.use_tpu = use_tpu\n",
+ " self.learning_rate = learning_rate\n",
+ " self.train_steps = train_steps\n",
+ " self.min_lr_ratio = min_lr_ratio\n",
+ " self.clip = clip\n",
+ " \n",
+ "training_parameters = Parameter(**training_parameters)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class BiAAttention:\n",
+ " def __init__(self, input_size_encoder, input_size_decoder, num_labels):\n",
+ " self.input_size_encoder = input_size_encoder\n",
+ " self.input_size_decoder = input_size_decoder\n",
+ " self.num_labels = num_labels\n",
+ " \n",
+ " self.W_d = tf.get_variable(\"W_d\", shape=[self.num_labels, self.input_size_decoder],\n",
+ " initializer=tf.contrib.layers.xavier_initializer())\n",
+ " self.W_e = tf.get_variable(\"W_e\", shape=[self.num_labels, self.input_size_encoder],\n",
+ " initializer=tf.contrib.layers.xavier_initializer())\n",
+ " self.U = tf.get_variable(\"U\", shape=[self.num_labels, self.input_size_decoder, self.input_size_encoder],\n",
+ " initializer=tf.contrib.layers.xavier_initializer())\n",
+ " \n",
+ " def forward(self, input_d, input_e, mask_d=None, mask_e=None):\n",
+ " batch = tf.shape(input_d)[0]\n",
+ " length_decoder = tf.shape(input_d)[1]\n",
+ " length_encoder = tf.shape(input_e)[1]\n",
+ " out_d = tf.expand_dims(tf.matmul(self.W_d, tf.transpose(input_d, [0, 2, 1])), 3)\n",
+ " out_e = tf.expand_dims(tf.matmul(self.W_e, tf.transpose(input_e, [0, 2, 1])), 2)\n",
+ " output = tf.matmul(tf.expand_dims(input_d, 1), self.U)\n",
+ " output = tf.matmul(output, tf.transpose(tf.expand_dims(input_e, 1), [0, 1, 3, 2]))\n",
+ " \n",
+ " output = output + out_d + out_e\n",
+ " \n",
+ " if mask_d is not None:\n",
+ " d = tf.expand_dims(tf.expand_dims(mask_d, 1), 3)\n",
+ " e = tf.expand_dims(tf.expand_dims(mask_e, 1), 2)\n",
+ " output = output * d * e\n",
+ " \n",
+ " return output\n",
+ " \n",
+ "class BiLinear:\n",
+ " def __init__(self, left_features, right_features, out_features):\n",
+ " self.left_features = left_features\n",
+ " self.right_features = right_features\n",
+ " self.out_features = out_features\n",
+ " \n",
+ " self.U = tf.get_variable(\"U-bi\", shape=[out_features, left_features, right_features],\n",
+ " initializer=tf.contrib.layers.xavier_initializer())\n",
+ " self.W_l = tf.get_variable(\"Wl\", shape=[out_features, left_features],\n",
+ " initializer=tf.contrib.layers.xavier_initializer())\n",
+ " self.W_r = tf.get_variable(\"Wr\", shape=[out_features, right_features],\n",
+ " initializer=tf.contrib.layers.xavier_initializer())\n",
+ " \n",
+ " def forward(self, input_left, input_right):\n",
+ " left_size = tf.shape(input_left)\n",
+ " output_shape = tf.concat([left_size[:-1], [self.out_features]], axis = 0)\n",
+ " batch = tf.cast(tf.reduce_prod(left_size[:-1]), tf.int32)\n",
+ " input_left = tf.reshape(input_left, (batch, self.left_features))\n",
+ " input_right = tf.reshape(input_right, (batch, self.right_features))\n",
+ " tiled = tf.tile(tf.expand_dims(input_left, axis = 0), (self.out_features,1,1))\n",
+ " output = tf.transpose(tf.reduce_sum(tf.matmul(tiled, self.U), axis = 2))\n",
+ " output = output + tf.matmul(input_left, tf.transpose(self.W_l))\\\n",
+ " + tf.matmul(input_right, tf.transpose(self.W_r))\n",
+ " \n",
+ " return tf.reshape(output, output_shape)\n",
+ "\n",
+ "class Attention:\n",
+ " def __init__(self, word_dim, num_words, char_dim, num_chars, num_filters, kernel_size,\n",
+ " hidden_size, encoder_layers, num_labels, arc_space, type_space):\n",
+ " \n",
+ " def cells(size, reuse=False):\n",
+ " return tf.nn.rnn_cell.LSTMCell(size,\n",
+ " initializer=tf.orthogonal_initializer(),reuse=reuse)\n",
+ " \n",
+ " self.word_embedd = tf.Variable(tf.random_uniform([num_words, word_dim], -1, 1))\n",
+ " self.char_embedd = tf.Variable(tf.random_uniform([num_chars, char_dim], -1, 1))\n",
+ " self.conv1d = tf.layers.Conv1D(num_filters, kernel_size, 1, padding='VALID')\n",
+ " self.num_labels = num_labels\n",
+ " self.encoder = tf.nn.rnn_cell.MultiRNNCell([cells(hidden_size) for _ in range(encoder_layers)])\n",
+ "\n",
+ " \n",
+ " \n",
+ " def encode(self, input_word, input_char):\n",
+ " word = tf.nn.embedding_lookup(self.word_embedd, input_word)\n",
+ " char = tf.nn.embedding_lookup(self.char_embedd, input_char)\n",
+ " b = tf.shape(char)[0]\n",
+ " wl = tf.shape(char)[1]\n",
+ " cl = tf.shape(char)[2]\n",
+ " d = char.shape[3]\n",
+ " char = tf.reshape(char, [b * wl, cl, d])\n",
+ " char = tf.reduce_max(self.conv1d(char), axis = 1)\n",
+ " char = tf.nn.tanh(char)\n",
+ " d = char.shape[-1]\n",
+ " char = tf.reshape(char, [b, wl, d])\n",
+ " \n",
+ " src_encoding = tf.concat([word, char], axis=2)\n",
+ " output, hn = tf.nn.dynamic_rnn(self.encoder, src_encoding, dtype = tf.float32,\n",
+ " scope = 'encoder')\n",
+ " arc_h = tf.nn.elu(self.arc_h(output))\n",
+ " arc_c = tf.nn.elu(self.arc_c(output))\n",
+ " \n",
+ " type_h = tf.nn.elu(self.type_h(output))\n",
+ " type_c = tf.nn.elu(self.type_c(output))\n",
+ " \n",
+ " return (arc_h, arc_c), (type_h, type_c), hn\n",
+ " \n",
+ " def forward(self, input_word, input_char, mask):\n",
+ " arcs, types, _ = self.encode(input_word, input_char)\n",
+ " \n",
+ " out_arc = tf.squeeze(self.attention.forward(arcs[0], arcs[1], mask_d=mask, mask_e=mask), axis = 1)\n",
+ " return out_arc, types, mask\n",
+ " \n",
+ " def loss(self, input_word, input_char, mask, heads, types):\n",
+ " out_arc, out_type, _ = self.forward(input_word, input_char, mask)\n",
+ " type_h, type_c = out_type\n",
+ " batch = tf.shape(out_arc)[0]\n",
+ " max_len = tf.shape(out_arc)[1]\n",
+ " batch_index = tf.range(0, batch)\n",
+ " t = tf.transpose(heads)\n",
+ " broadcasted = tf.broadcast_to(batch_index, tf.shape(t))\n",
+ " concatenated = tf.transpose(tf.concat([tf.expand_dims(broadcasted, axis = 0), \n",
+ " tf.expand_dims(t, axis = 0)], axis = 0))\n",
+ " type_h = tf.gather_nd(type_h, concatenated)\n",
+ " out_type = self.bilinear.forward(type_h, type_c)\n",
+ " minus_inf = -1e8\n",
+ " minus_mask = (1 - mask) * minus_inf\n",
+ " out_arc = out_arc + tf.expand_dims(minus_mask, axis = 2) + tf.expand_dims(minus_mask, axis = 1)\n",
+ " loss_arc = tf.nn.log_softmax(out_arc, dim=1)\n",
+ " loss_type = tf.nn.log_softmax(out_type, dim=2)\n",
+ " loss_arc = loss_arc * tf.expand_dims(mask, axis = 2) * tf.expand_dims(mask, axis = 1)\n",
+ " loss_type = loss_type * tf.expand_dims(mask, axis = 2)\n",
+ " num = tf.reduce_sum(mask) - tf.cast(batch, tf.float32)\n",
+ " child_index = tf.tile(tf.expand_dims(tf.range(0, max_len), 1), [1, batch])\n",
+ " t = tf.transpose(heads)\n",
+ " broadcasted = tf.broadcast_to(batch_index, tf.shape(t))\n",
+ " concatenated = tf.transpose(tf.concat([tf.expand_dims(broadcasted, axis = 0),\n",
+ " tf.expand_dims(t, axis = 0),\n",
+ " tf.expand_dims(child_index, axis = 0)], axis = 0))\n",
+ " loss_arc = tf.gather_nd(loss_arc, concatenated)\n",
+ " loss_arc = tf.transpose(loss_arc, [1, 0])\n",
+ " \n",
+ " t = tf.transpose(types)\n",
+ " broadcasted = tf.broadcast_to(batch_index, tf.shape(t))\n",
+ " concatenated = tf.transpose(tf.concat([tf.expand_dims(broadcasted, axis = 0),\n",
+ " tf.expand_dims(child_index, axis = 0),\n",
+ " tf.expand_dims(t, axis = 0)], axis = 0))\n",
+ " loss_type = tf.gather_nd(loss_type, concatenated)\n",
+ " loss_type = tf.transpose(loss_type, [1, 0])\n",
+ " return tf.reduce_sum(-loss_arc) / num, tf.reduce_sum(-loss_type) / num\n",
+ " \n",
+ " def decode(self, input_word, input_char, mask, leading_symbolic=0):\n",
+ " out_arc, out_type, _ = self.forward(input_word, input_char, mask)\n",
+ " batch = tf.shape(out_arc)[0]\n",
+ " max_len = tf.shape(out_arc)[1]\n",
+ " sec_max_len = tf.shape(out_arc)[2]\n",
+ " out_arc = out_arc + tf.linalg.diag(tf.fill([max_len], -np.inf))\n",
+ " minus_mask = tf.expand_dims(tf.cast(1 - mask, tf.bool), axis = 2)\n",
+ " minus_mask = tf.tile(minus_mask, [1, 1, sec_max_len])\n",
+ " out_arc = tf.where(minus_mask, tf.fill(tf.shape(out_arc), -np.inf), out_arc)\n",
+ " heads = tf.argmax(out_arc, axis = 1)\n",
+ " type_h, type_c = out_type\n",
+ " batch = tf.shape(type_h)[0]\n",
+ " max_len = tf.shape(type_h)[1]\n",
+ " batch_index = tf.range(0, batch)\n",
+ " t = tf.cast(tf.transpose(heads), tf.int32)\n",
+ " broadcasted = tf.broadcast_to(batch_index, tf.shape(t))\n",
+ " concatenated = tf.transpose(tf.concat([tf.expand_dims(broadcasted, axis = 0), \n",
+ " tf.expand_dims(t, axis = 0)], axis = 0))\n",
+ " type_h = tf.gather_nd(type_h, concatenated)\n",
+ " out_type = self.bilinear.forward(type_h, type_c)\n",
+ " out_type = out_type[:, :, leading_symbolic:]\n",
+ " types = tf.argmax(out_type, axis = 2)\n",
+ " return heads, types\n",
+ " \n",
+ "class Model:\n",
+ " def __init__(\n",
+ " self,\n",
+ " learning_rate,\n",
+ " hidden_size_word,\n",
+ " cov = 0.0):\n",
+ " \n",
+ " self.words = tf.placeholder(tf.int32, (None, None))\n",
+ " self.segment_ids = tf.placeholder(tf.int32, [None, None])\n",
+ " self.input_masks = tf.placeholder(tf.float32, [None, None])\n",
+ " self.heads = tf.placeholder(tf.int32, (None, None))\n",
+ " self.types = tf.placeholder(tf.int32, (None, None))\n",
+ " self.mask = tf.cast(tf.math.not_equal(self.words, 0), tf.float32)\n",
+ " self.maxlen = tf.shape(self.words)[1]\n",
+ " self.lengths = tf.count_nonzero(self.words, 1)\n",
+ " mask = self.mask\n",
+ " heads = self.heads\n",
+ " types = self.types\n",
+ " \n",
+ " self.arc_h = tf.layers.Dense(hidden_size_word)\n",
+ " self.arc_c = tf.layers.Dense(hidden_size_word)\n",
+ " self.attention = BiAAttention(hidden_size_word, hidden_size_word, 1)\n",
+ "\n",
+ " self.type_h = tf.layers.Dense(hidden_size_word)\n",
+ " self.type_c = tf.layers.Dense(hidden_size_word)\n",
+ " self.bilinear = BiLinear(hidden_size_word, hidden_size_word, len(tag2idx))\n",
+ " \n",
+ " xlnet_model = xlnet.XLNetModel(\n",
+ " xlnet_config=xlnet_config,\n",
+ " run_config=xlnet_parameters,\n",
+ " input_ids=tf.transpose(self.words, [1, 0]),\n",
+ " seg_ids=tf.transpose(self.segment_ids, [1, 0]),\n",
+ " input_mask=tf.transpose(self.input_masks, [1, 0]))\n",
+ " output_layer = xlnet_model.get_sequence_output()\n",
+ " output_layer = tf.transpose(output_layer, [1, 0, 2])\n",
+ " \n",
+ " arc_h = tf.nn.elu(self.arc_h(output_layer))\n",
+ " arc_c = tf.nn.elu(self.arc_c(output_layer))\n",
+ " \n",
+ " type_h = tf.nn.elu(self.type_h(output_layer))\n",
+ " type_c = tf.nn.elu(self.type_c(output_layer))\n",
+ " \n",
+ " out_arc = tf.squeeze(self.attention.forward(arc_h, arc_h, mask_d=self.mask, \n",
+ " mask_e=self.mask), axis = 1)\n",
+ " \n",
+ " batch = tf.shape(out_arc)[0]\n",
+ " max_len = tf.shape(out_arc)[1]\n",
+ " sec_max_len = tf.shape(out_arc)[2]\n",
+ " batch_index = tf.range(0, batch)\n",
+ " \n",
+ " decode_arc = out_arc + tf.linalg.diag(tf.fill([max_len], -np.inf))\n",
+ " minus_mask = tf.expand_dims(tf.cast(1 - mask, tf.bool), axis = 2)\n",
+ " minus_mask = tf.tile(minus_mask, [1, 1, sec_max_len])\n",
+ " decode_arc = tf.where(minus_mask, tf.fill(tf.shape(decode_arc), -np.inf), decode_arc)\n",
+ " self.heads_seq = tf.argmax(decode_arc, axis = 1)\n",
+ " \n",
+ " t = tf.cast(tf.transpose(self.heads_seq), tf.int32)\n",
+ " broadcasted = tf.broadcast_to(batch_index, tf.shape(t))\n",
+ " concatenated = tf.transpose(tf.concat([tf.expand_dims(broadcasted, axis = 0), \n",
+ " tf.expand_dims(t, axis = 0)], axis = 0))\n",
+ " type_h = tf.gather_nd(type_h, concatenated)\n",
+ " out_type = self.bilinear.forward(type_h, type_c)\n",
+ " self.tags_seq = tf.argmax(out_type, axis = 2)\n",
+ " \n",
+ " batch = tf.shape(out_arc)[0]\n",
+ " max_len = tf.shape(out_arc)[1]\n",
+ " batch_index = tf.range(0, batch)\n",
+ " t = tf.transpose(heads)\n",
+ " broadcasted = tf.broadcast_to(batch_index, tf.shape(t))\n",
+ " concatenated = tf.transpose(tf.concat([tf.expand_dims(broadcasted, axis = 0), \n",
+ " tf.expand_dims(t, axis = 0)], axis = 0))\n",
+ " type_h = tf.gather_nd(type_h, concatenated)\n",
+ " out_type = self.bilinear.forward(type_h, type_c)\n",
+ " minus_inf = -1e8\n",
+ " minus_mask = (1 - mask) * minus_inf\n",
+ " out_arc = out_arc + tf.expand_dims(minus_mask, axis = 2) + tf.expand_dims(minus_mask, axis = 1)\n",
+ " loss_arc = tf.nn.log_softmax(out_arc, dim=1)\n",
+ " loss_type = tf.nn.log_softmax(out_type, dim=2)\n",
+ " loss_arc = loss_arc * tf.expand_dims(mask, axis = 2) * tf.expand_dims(mask, axis = 1)\n",
+ " loss_type = loss_type * tf.expand_dims(mask, axis = 2)\n",
+ " num = tf.reduce_sum(mask) - tf.cast(batch, tf.float32)\n",
+ " child_index = tf.tile(tf.expand_dims(tf.range(0, max_len), 1), [1, batch])\n",
+ " t = tf.transpose(heads)\n",
+ " broadcasted = tf.broadcast_to(batch_index, tf.shape(t))\n",
+ " concatenated = tf.transpose(tf.concat([tf.expand_dims(broadcasted, axis = 0),\n",
+ " tf.expand_dims(t, axis = 0),\n",
+ " tf.expand_dims(child_index, axis = 0)], axis = 0))\n",
+ " loss_arc = tf.gather_nd(loss_arc, concatenated)\n",
+ " loss_arc = tf.transpose(loss_arc, [1, 0])\n",
+ " \n",
+ " t = tf.transpose(types)\n",
+ " broadcasted = tf.broadcast_to(batch_index, tf.shape(t))\n",
+ " concatenated = tf.transpose(tf.concat([tf.expand_dims(broadcasted, axis = 0),\n",
+ " tf.expand_dims(child_index, axis = 0),\n",
+ " tf.expand_dims(t, axis = 0)], axis = 0))\n",
+ " loss_type = tf.gather_nd(loss_type, concatenated)\n",
+ " loss_type = tf.transpose(loss_type, [1, 0])\n",
+ " self.cost = (tf.reduce_sum(-loss_arc) / num) + (tf.reduce_sum(-loss_type) / num)\n",
+ " self.optimizer = tf.train.AdamOptimizer(\n",
+ " learning_rate = learning_rate\n",
+ " ).minimize(self.cost)\n",
+ " \n",
+ " mask = tf.sequence_mask(self.lengths, maxlen = self.maxlen)\n",
+ " \n",
+ " self.prediction = tf.boolean_mask(self.tags_seq, mask)\n",
+ " mask_label = tf.boolean_mask(self.types, mask)\n",
+ " correct_pred = tf.equal(tf.cast(self.prediction, tf.int32), mask_label)\n",
+ " correct_index = tf.cast(correct_pred, tf.float32)\n",
+ " self.accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n",
+ " \n",
+ " self.prediction = tf.cast(tf.boolean_mask(self.heads_seq, mask), tf.int32)\n",
+ " mask_label = tf.boolean_mask(self.heads, mask)\n",
+ " correct_pred = tf.equal(self.prediction, mask_label)\n",
+ " correct_index = tf.cast(correct_pred, tf.float32)\n",
+ " self.accuracy_depends = tf.reduce_mean(tf.cast(correct_pred, tf.float32))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "WARNING:tensorflow:From /home/husein/.local/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py:507: calling count_nonzero (from tensorflow.python.ops.math_ops) with axis is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "reduction_indices is deprecated, use axis instead\n",
+ "WARNING:tensorflow:\n",
+ "The TensorFlow contrib module will not be included in TensorFlow 2.0.\n",
+ "For more information, please see:\n",
+ " * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n",
+ " * https://github.com/tensorflow/addons\n",
+ " * https://github.com/tensorflow/io (for I/O related ops)\n",
+ "If you depend on functionality not listed there, please file an issue.\n",
+ "\n",
+ "WARNING:tensorflow:From /home/husein/testing/xlnet.py:253: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.\n",
+ "\n",
+ "WARNING:tensorflow:From /home/husein/testing/xlnet.py:253: The name tf.AUTO_REUSE is deprecated. Please use tf.compat.v1.AUTO_REUSE instead.\n",
+ "\n",
+ "WARNING:tensorflow:From /home/husein/testing/modeling.py:686: The name tf.logging.info is deprecated. Please use tf.compat.v1.logging.info instead.\n",
+ "\n",
+ "INFO:tensorflow:memory input None\n",
+ "INFO:tensorflow:Use float type \n",
+ "WARNING:tensorflow:From /home/husein/testing/modeling.py:693: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.\n",
+ "\n",
+ "WARNING:tensorflow:From /home/husein/testing/modeling.py:797: dropout (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "Use keras.layers.dropout instead.\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:From /home/husein/testing/modeling.py:99: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "Use keras.layers.dense instead.\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING: Entity > could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output. Cause: converting >: AssertionError: Bad argument number for Name: 3, expecting 4\n",
+ "WARNING:tensorflow:Entity