optiluca

import numpy as np
from keras.layers.core import Dense, Activation, Dropout
from keras.layers import CuDNNLSTM, LSTM
from keras.models import Sequential
from keras.models import load_model
from keras import optimizers
from keras.engine.saving import preprocess_weights_for_loading

sample_size = 100

alexeygrigorev

pip install grpcio-tools

wget https://github.com/tensorflow/tensorflow/archive/v1.9.0.zip -O tf-190.zip
unzip tf-190.zip && rm tf-190.zip

wget https://github.com/tensorflow/serving/archive/1.9.0.zip -O tf-serving-190.zip
unzip tf-serving-190.zip && rm tf-serving-190.zip

mv serving-1.9.0/tensorflow_serving tensorflow-1.9.0

melgor

berkedel

How to solve dyld: Library not loaded: /usr/local/opt/icu4c/lib/libicui18n.60.dylib

brew uninstall --ignore-dependencies node icu4c
brew install node

renexu

import threading

from keras.applications.inception_v3 import InceptionV3
from keras.optimizers import Adam
from keras.utils.io_utils import HDF5Matrix


class threadsafe_iter:
    """Takes an iterator/generator and makes it thread-safe by
    serializing call to the `next` method of given iterator/generator.

joemarshall

# I just put this in so you can see why it matters

class CUDNNCompatible_GRUCell(keras.layers.Layer):
    """Cell class for the GRU layer which is compatible with CuDNN GRU cells (but doesn't require tensorflow/Cuda).
    # Arguments
        units: Positive integer, dimensionality of the output space.
        activation: Activation function to use
            (see [activations](../activations.md)).
            If you pass None, no activation is applied
            (ie. "linear" activation: `a(x) = x`).

jjallaire

'''Train MNIST with tfrecords yielded from a TF Dataset

In order to run this example you should first run 'mnist_to_tfrecord.py'
which will download MNIST data and serialize it into 3 tfrecords files
(train.tfrecords, validation.tfrecords, and test.tfrecords).

This example demonstrates the use of TF Datasets wrapped by a generator
function. The example currently only works with a fork of keras that accepts
`workers=0` as an argument to fit_generator, etc. Passing `workers=0` results
in the generator function being run on the main thread (without this various

aallan

#!/usr/bin/env python3
# Copyright 2017 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software

jganzabal

This configuration worked for me, hope it helps

It is based on: https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b

and on: https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support

Hardware

iteufel

# ************************************************************
# Sequel Pro SQL dump
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