<jupyter_start><jupyter_text>Train<jupyter_code>import sys

sys.path.insert(0, '..')
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers<jupyter_output>/Users/hotbaby/Library/Python/3.7/lib/python/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'.
  _np_qint8 = np.dtype([("qint8", np.int8, 1)])
/Users/hotbaby/Library/Python/3.7/lib/python/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'.
  _np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/Users/hotbaby/Library/Python/3.7/lib/python/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'.
  _np_qint16 = np.dtype([("qint16", np.int16, 1)])
/Users/hotbaby/Library/Python/3.7/lib/python/site-packages[...]<jupyter_text>Models  GRU model<jupyter_code>inputs = keras.Input(shape=(784,), name='img')
x = layers.Dense(64, activation='relu')(inputs)
x = layers.Dense(64, activation='relu')(x)
outputs = layers.Dense(10, activation='softmax')(x)

model = keras.Model(inputs=inputs, outputs=outputs, name='mnist_model')

model.summary()
from senti_analysis.gru_model import model
model.summary()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15805849408836342, 'fraction_numerical': 0.03360298693217175, 'mean_word_length': 5.7280334728033475, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 8, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '358354', 'license': 'MIT', 'n_tokens_mistral': 616, 'n_tokens_neox': 588, 'n_words': 134, 'path': 'notebooks/train.ipynb', 'repo_name': 'hotbaby/sentiment-analysis', 'size': '1607'}