iamsurya

// Leetcode https://leetcode.com/problems/min-stack
// What's a min stack? A min stack is a stack (first in, last out) that also tracks the minimum value at any given point of time.
// push, pop, top and min element need to be constant time.

class StackNode{
    public:
    int val;
    int minval;
    
    StackNode(int x, int min): val(x), minval(min) {};

iamsurya

// From https://github.com/gameplay3d/GamePlay/blob/master/gameplay/src/PlatformAndroid.cpp
// Line 1373

{
 // Prepare to monitor accelerometer.
    __sensorManager = ASensorManager_getInstance();
    __accelerometerSensor = ASensorManager_getDefaultSensor(__sensorManager, ASENSOR_TYPE_ACCELEROMETER);
    __gyroscopeSensor = ASensorManager_getDefaultSensor(__sensorManager, ASENSOR_TYPE_GYROSCOPE);
    __sensorEventQueue = ASensorManager_createEventQueue(__sensorManager, __state->looper, LOOPER_ID_USER, NULL, NULL);
    

iamsurya

// Code to use a frozen pb model and run inferences in C using libtensorflow
// Adapted from https://github.com/PatWie/tensorflow-cmake/blob/master/inference/c/inference_c.c

#include "pch.h"
#include <stdlib.h>
#include <iostream>
#include <c_api.h>

/* Functions to help read pb file */
void free_buffer(void* data, size_t length) { free(data); }

iamsurya

/* Add appropriate headers here */
// #include<iostream.h>
// #include<stdio.h>

#include <c_api.h>

int main()
{
	printf("Hello from TensorFlow C library version %s\n", TF_Version());

iamsurya

echo EXPORTS > D:\libtensorflow\tensorflow.def
for /f "usebackq tokens=4,* delims=_ " %i in (`dumpbin /exports "D:\libtensorflow\tensorflow.dll"`) do if %i==TF echo %i_%j >> D:\libtensorflow\tensorflow.def
lib /def:"D:\libtensorflow\tensorflow.def" /out:"D:\libtensorflow\tensorflow.lib" /machine:x64          

iamsurya

from tensorflow.python.platform import gfile
with tf.Session() as sess:
    with gfile.FastGFile('slopemodel/slopemodel.pb', 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        sess.graph.as_default()
        g_in = tf.import_graph_def(graph_def)
    tensor_output = sess.graph.get_tensor_by_name('import/dense_2/Sigmoid:0')
    tensor_input = sess.graph.get_tensor_by_name('import/dense_1_input:0')
    predictions = sess.run(tensor_output, {tensor_input:sample})

iamsurya

import/dense_1_input
import/dense_1/kernel
import/dense_1/kernel/read
import/dense_1/bias
import/dense_1/bias/read
import/dense_1/MatMul
import/dense_1/BiasAdd
import/dense_1/Relu
import/dense_2/kernel
import/dense_2/kernel/read

iamsurya

from tensorflow.python.platform import gfile
with tf.Session() as sess:
    with gfile.FastGFile('slopemodel/slopemodel.pb', 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        sess.graph.as_default()
        g_in = tf.import_graph_def(graph_def)
    for op in tf.get_default_graph().get_operations():
        print(str(op.name))
    for n in tf.get_default_graph().as_graph_def().node:

iamsurya

sample = normdata[1].reshape((1,21))

iamsurya

0	603	596	578	548	539	532	533	513	494	497	505	483	461	463	445	443	431	426	406	390	397
1	552	557	554	575	592	608	611	617	623	634	637	660	694	687	703	717	723	710	732	744	746
1	746	770	804	794	818	824	831	831	849	858	864	875	877	897	892	896	907	907	919	924	950
0	432	433	424	416	411	396	381	376	377	361	361	361	349	331	325	300	309	297	297	275	275
0	363	354	341	328	319	302	289	279	256	245	228	226	211	204	197	188	161	160	146	139	118
1	425	429	439	460	456	443	471	476	499	489	507	519	523	540	545	545	555	563	558	554	569
1	463	461	462	479	494	501	518	513	526	543	576	592	593	599	603	607	616	625	623	644	663
0	374	383	372	383	368	354	335	324	316	310	313	299	259	262	248	239	234	223	205	197	191
1	553	572	590	581	577	592	603	608	639	642	669	670	681	685	702	702	713	712	722	750	754
0	403	388	392	389	371	363	339	324	302	281	271	264	240	251	246	234	219	220	198	179	176