hgaiser

hgaiser

'''Trains a simple convnet on the MNIST dataset.

Gets to 99.25% test accuracy after 12 epochs
(there is still a lot of margin for parameter tuning).
16 seconds per epoch on a GRID K520 GPU.
'''

from __future__ import print_function
import tensorflow as tf
from tensorflow.keras.datasets import mnist

hgaiser

#include "fizyr_flow.hpp"

void Variable::operator=(std::any v) {
	// Copy the new value.
	value = v;

	// Check if we can run ops that haven't been executed yet.
	for (auto const & op: operators)
		if (op->inputsReady() && !op->executed()) {
			op->_execute();

hgaiser

#!/usr/bin/env python

"""
Copyright 2017-2018 Fizyr (https://fizyr.com)

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

hgaiser

name: "ResNet-18"

layer {
	name: 'input-data'
	type: 'Python'
	top: 'data'
	top: 'im_info'
	top: 'gt_boxes'
	python_param {
		module: 'roi_data_layer.layer'

hgaiser

hgaiser

hgaiser

hgaiser

hgaiser