gaphex’s gists

gaphex / projector_config.json

Created February 21, 2020 08:21

	{
	"embeddings": [
	{
	"tensorName": "Intent40",
	"tensorShape": [
	1360,
	768
	],
	"tensorPath": "https://gist.githubusercontent.com/gaphex/d56f0124a7b7459408d92bbaca373f3e/raw/abb29897ab1015d7e05d9eda90514aeb45181953/embeddings.tsv",
	"metadataPath": "https://gist.githubusercontent.com/gaphex/2793c044577abc73cff7d438a2097ef1/raw/014ab59be93252b9516c0883d21dba6a9b0622ad/metadata.tsv"

gaphex / metadata.tsv

Created February 21, 2020 08:17

Label	Id	Sentence
blagotvoritelnost_212	0	греф_помогает_тяжело_больным
blagotvoritelnost_212	0	греф_миллиардер
blagotvoritelnost_212	0	может_поможете_бедным_у_вас_же_много_денег
blagotvoritelnost_212	0	сбербанк_заботится_о_больных
blagotvoritelnost_212	0	сбербанк_помогает_людям
blagotvoritelnost_212	0	грефу_только_денег_не_надо
blagotvoritelnost_212	0	сбербанк_заботится_о_ветеранах
blagotvoritelnost_212	0	грефу_только_денег_не_надо
blagotvoritelnost_212	0	греф_помогает_научному_прогрессу

gaphex / embeddings.tsv

Created February 21, 2020 08:15

We can't make this file beautiful and searchable because it's too large.

-0.033	-0.578	0.1926	0.2186	-0.5674	0.2001	0.4424	-0.2903	0.1769	0.355	0.2542	-1.124	0.1263	-0.5547	0.157	-0.1073	-0.02002	-0.1493	0.02702	0.1525	0.1299	0.3364	0.276	-0.004074	-0.3472	0.4946	-0.1622	0.3628	0.03714	0.3384	0.3384	-0.4062	-0.392	-0.3782	0.2084	0.09204	-0.01868	0.1995	-0.03073	0.4304	0.087	-0.04553	-0.6196	0.05472	0.337	0.4192	0.4705	-0.2595	-0.2952	-1.256	-0.10583	0.4216	-0.03677	0.04718	-0.414	0.651	-0.1908	0.2788	-0.125	0.1112	-0.3457	-0.4543	0.256	0.444	0.372	0.007282	0.254	-0.0879	-0.9517	0.1906	0.0641	0.3645	0.09	-0.4607	-0.4106	-0.1879	0.4492	0.12067	-0.1442	0.3267	0.1013	-0.4993	-0.2394	0.814	-0.2183	0.3274	-0.2252	-0.02669	0.2515	-0.457	-0.0087	-0.6934	0.312	0.1274	-0.3042	0.05402	-0.06024	-0.3518	0.5913	0.063	-0.4602	-0.6064	-0.04974	-0.01523	0.4531	-0.07745	-0.01627	0.2477	0.2498	-0.02473	0.10626	0.164	0.3872	-0.4756	0.2184	-0.7964	-0.3525	0.4448	0.02672	-0.432	0.1124	0.3257	0.3655	-0.203	-0.2278	0.01701	0.1403	0.235	0.0183	-0.1366	-0.5996	0.1203	0.3403	0.04422	-0.16	-0.657	0.362	-0.18

gaphex / finetuning_example.py

Created December 10, 2019 11:40

Binary classification with BertLayer

	inp = tf.keras.Input(shape=(1,), dtype=tf.string)
	encoder = BertLayer(bert_path="./bert-module/", seq_len=48,
	tune_embeddings=False, do_preprocessing=True,
	pooling='cls', n_tune_layers=3, verbose=False)

	pred = tf.keras.layers.Dense(1, activation='sigmoid')(encoder(inp))
	model = tf.keras.models.Model(inputs=[inp], outputs=[pred])

	model.compile(optimizer="adam", loss="binary_crossentropy", metrics=["accuracy"])
	model.fit(trX, trY, validation_data=[tsX, tsY], batch_size=128, epochs=5)

gaphex / run_inference.py

Created November 28, 2019 16:34

	sess = tf.Session(graph=restored_graph)

	t_data = ["What would happen if earth stopped rotating? \|\|\| What would happen if the Earth rotation suddenly stop?"]

	y_out = sess.run(y, feed_dict={
	x: np.array(t_data).reshape((-1,1))
	})

	y_out

gaphex / build_preprocessor_op.py

Created November 28, 2019 16:27

	preprocessor = build_preprocessor("./uncased_L-12_H-768_A-12/vocab.txt", 64)
	py_func = tf.numpy_function(preprocessor, [x], [tf.int32, tf.int32, tf.int32], name='preprocessor')

gaphex / get_io_op_name.py

Last active November 28, 2019 16:24

	graph_ops = restored_graph.get_operations()
	input_op, output_op = graph_ops[0].name, graph_ops[-1].name

	x = restored_graph.get_tensor_by_name(input_op + ':0')
	y = restored_graph.get_tensor_by_name(output_op + ':0')

gaphex / restore_graph.py

Created November 27, 2019 21:13

	def load_graph(frozen_graph_filename):
	with tf.gfile.GFile(frozen_graph_filename, "rb") as f:
	graph_def = tf.GraphDef()
	graph_def.ParseFromString(f.read())

	with tf.Graph().as_default() as graph:
	tf.import_graph_def(graph_def)
	return graph

	restored_graph = load_graph("frozen_graph.pb")

gaphex / serialize_graph.py

Last active November 30, 2019 19:04

frozen_graph = freeze_keras_model(model, export_path="frozen_graph.pb")

gaphex / freeze_model.py

Last active August 10, 2020 17:27

	from tensorflow.python.framework.graph_util import convert_variables_to_constants
	from tensorflow.python.tools.optimize_for_inference_lib import optimize_for_inference

	def freeze_keras_model(model, export_path=None, clear_devices=True):
	"""
	Freezes the state of a session into a pruned computation graph.

	@param model The Keras model to be optimized for inference.
	@param clear_devices Remove the device directives from the graph for better portability.
	@return The frozen graph definition.

Denis gaphex