| № | Район | Название | Дома |
|---|---|---|---|
| 0 | Адмиралтейский | 1-я Красноармейская улица | 1/21А, 1/21Д, 1/21Ж, 1/21З, 1/21К, 2, 2В, 3-5-7-9А, 3-5-7-9Б, 4, 6, 6Б, 8-10, 8-10Б, 11, 11В, 12, 13, 13Б, 13В, 14, 15, 16, 18, 18Б, 20, 22, 24, 24Б |
| 1 | Адмиралтейский | 10-я Красноармейская улица | 3, 3б, 4, 5, 5а, 5Б, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16А, 17, 19, 19А, 19Б1, 20, 20а, 21, 22, 23, 24, 26 |
| 2 | Адмиралтейский | 11-я Красноармейская улица | 1, 2, 4, 5/13, 6, 7, 8, 9, 10, 11, 11А, 11В, 11Ж, 12, 13, 14, 15а, 15аБ, 15Б, 16, 18, 20, 22, 26, 28 |
| 3 | Адмиралтейский | 12-я Красноармейская улица | 1, 2, 3, 4, 5, 6, 6Б, 6Г, 7, 8, 8Б, 8В, 10, 11, 12, 12Б, 13, 14, 14В, 15, 16Г, 16Н, 17, 19, 21, 23, 24, 25, 27, 29, 32, 33А, 34, 36, 37, 40 |
| 4 | Адмиралтейский | [13-я Красноармейская улица](http://spb.ginfo.ru/ulicy |
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| @tf.function | |
| def model(x, w0, b0, w1, b1, ...): | |
| x = tf.nn.sigmoid(tf.matmul(x, w0) + b0) | |
| x = tf.nn.sigmoid(tf.matmul(x, w1) + b1) | |
| return x | |
| def train(...): | |
| for (x,y) in train_ds: | |
| with tf.GradientTape() as tape: | |
| loss = compute_loss(model(x, ...), y) |
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| @tf.function | |
| def model(x, w0, b0, w1, b1, ...): | |
| x = tf.nn.sigmoid(tf.matmul(x, w0) + b0) | |
| x = tf.nn.sigmoid(tf.matmul(x, w1) + b1) | |
| return x | |
| def train(...): | |
| for (x,y) in train_ds: | |
| with tf.GradientTape() as tape: | |
| loss = compute_loss(model(x, ...), y) |
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| inputs = keras.Input(shape=(784,), name='digits') | |
| x = layers.Dense(64, activation='relu', name='dense_1')(inputs) | |
| x = layers.Dense(64, activation='relu', name='dense_2')(x) | |
| outputs = layers.Dense(10, activation='softmax', name='predictions')(x) | |
| model = keras.Model(inputs=inputs, outputs=outputs) | |
| model.fit(...) |
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| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| import tensorflow as tf | |
| import copy | |
| import json | |
| import math | |
| import six | |
| import itertools |
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| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| import copy | |
| import json | |
| import math | |
| import six | |
| import tensorflow as tf | |
| import itertools |
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| # Instructions | |
| # 1. Load this file in IPython | |
| # 2. call `run()` | |
| # 3. Interrupt it with Ctrl+C | |
| # 4. See no global state changed | |
| from typing import Any,Optional | |
| from time import sleep | |
| class Model: |
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| import os | |
| import json | |
| os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' | |
| import tensorflow as tf | |
| assert tf.version.VERSION.startswith('2.') | |
| gpus = tf.config.experimental.list_physical_devices('GPU') | |
| tf.config.experimental.set_virtual_device_configuration( | |
| gpus[0], | |
| [tf.config.experimental.VirtualDeviceConfiguration(memory_limit=5.5*1024)]) |
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| #!/bin/sh | |
| # VKontakte *m3u8 downloader | |
| # Worked at the time of writing | |
| mkdir /tmp/m3u8 | |
| set -e -x | |
| cd /tmp/m3u8 | |
| rm * |
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| <html> | |
| <head> | |
| <script> | |
| function clearclass(item, cls) { | |
| item.classList.remove(cls); | |
| } | |
| function setclass(item, cls) { | |
| item.classList.add(cls); |