#! /bin/bash
#############################
#   TF 1.7 Testing Script   #
#############################

#TF Session
python tf_keras_mnist.py

# TF Eager
python mnist_eager.py

# Keras Test
python keras_mnist_test.py


#TODO Move from tf.tf_cnn_benchmarks to perfzero https://github.com/tensorflow/benchmarks/tree/master/perfzero

# # Delete benchmarks folder if exists
# if test -d benchmarks; then
# 	rm -rf benchmarks
# fi

# Clone Benchmarks and go to a certain commit
# git clone https://github.com/tensorflow/benchmarks.git
# cd benchmarks/scripts/tf_cnn_benchmarks

# # Check if GPU is installed (quick hack)
# which nvidia-smi &> /dev/null
# ISGPU=$?

# if test $ISGPU -eq 1; then
# 	# CPU or CPU2?
# 	NCORE=`cat /proc/cpuinfo | grep processor | wc -l`

# 	# Quick Benchmark on AlexNet (syntethic images, no data transformation, channel last)
# 	if test $NCORE -eq 2; then
# 		# CPU test (defined initial lr otherwise Loss is NaN )
# 		python tf_cnn_benchmarks.py --device=cpu  --kmp_blocktime=0 --nodistortions --model=alexnet --data_format=NHWC --batch_size=32  --num_inter_threads=1 --num_intra_threads=$NCORE --init_learning_rate=0.00001
# 	else
# 		# CPU2 test
# 		python tf_cnn_benchmarks.py --device=cpu  --kmp_blocktime=0 --nodistortions --model=alexnet --data_format=NHWC --batch_size=64  --num_inter_threads=1 --num_intra_threads=$NCORE --init_learning_rate=0.00001
# 	fi
# else
# 	GPU_DEV_NAME=$(python -c 'from __future__ import print_function; import tensorflow as tf; print(tf.test.gpu_device_name())' 2> /dev/null)
# 	case ${GPU_DEV_NAME} in
# 	/device:GPU:*)
# 		echo "GPU load test passed. Device found: ${GPU_DEV_NAME}"
# 		;;
# 	*)
# 		echo "ERROR: Tensorflow not able to find GPU device! Device found: ${GPU_DEV_NAME}"
# 		exit 1
# 		;;
# 	esac

# 	# GPU or GPU2?
# 	nvidia-smi | grep -q V100
# 	ISV100=$?

# 	# Quick Benchmark on Resnet-50 (syntethic images, no data transformation, channel first)
# 	if test $ISV100 -eq 1; then
# 		# GPU test
# 		python tf_cnn_benchmarks.py --device=gpu --num_gpus=1 --batch_size=64 --model=resnet50 --nodistortions --data_format=NCHW
# 	else
# 		# GPU2 test (with MXP)
# 		python tf_cnn_benchmarks.py --device=gpu --num_gpus=1 --batch_size=256 --model=resnet50 --nodistortions --data_format=NCHW --use_fp16=true
# 	fi
# fi

