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development]**\n\n# TPU-optimized U-Net model implementation \n\n### Model description\nThis repository contains U-Net model implementation (originally proposed in [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://arxiv.org/abs/1505.04597))\nwith usage of Tensoflow TPUEstimators API.\n\n##### Model architecture\n\n### Training U-Net on Cloud TPU\n\n##### Config your TPU flock:\n\nCheck your current Cloud TPU configuration (in Google Cloud Shell):\n```bash\nctpu print-config\n```\n\nAs a result you should get the similar outcome\n```bash\nctpu configuration:\n        name: your-user-name\n        project: your-project-name\n        zone: your-zone\n```\n\nTo run CTPU flock, in Google Cloud Shell, execute the following command\n```bash\nZONE=YOUR-ZONE\nTPU_NAME=YOUR-TPU-NAME\n\nctpu up --zone $ZONE --name $TPU_NAME\n```\n\nOnce the CTPU flock is ready, ssh to your instance\n```bash\nGCP_PROJECT=YOUR-GCP-PROJECT\n\ngcloud compute --project $GCP_PROJECT ssh --zone $ZONE $TPU_NAME\n```\n\n##### Create bucket for storing training checkpoints:\n\nExecute the following commands to create a bucket on your TPU VM instance:\n```bash\nGCP_PROJECT=YOUR-GCP-PROJECT\nMODEL_DIR=gs://YOUR-GOOGLE-CLOUD-BUCKET\n\ngsutil mb -p $GCP_PROJECT $MODEL_DIR\n```\n\n##### Training U-Net model as a classifier on Cloud TPU\n\nIn order to train your MNIST image classifier based on U-Net architecture and with the usage of Cloud TPU\nuse **u_net_clf_tpu.py** script with the following parameters:\n```bash\n# TPU configuration\nGCP_PROJECT=YOUR-GCP-PROJECT\nTPU_ZONE=YOUR-TPU-ZONE\nTPU_NAME=YOUR-TPU-NAME\nMODEL_DIR=gs://YOUR-GOOGLE-CLOUD-BUCKET\n\n# problem/model configuration\nPROBLEM=MNIST\nTRAIN_DIR=PATH-TO-TRAIN-DIR\nEVAL_DIR=PATH-TO-EVALUATION-DIR\n\npython u_net_clf_tpu.py \\\n--train_dir=$TRAIN_DIR \\\n--eval_dir=$EVAL_DIR \\\n--problem=$PROBLEM \\\n--model_dir=$MODEL_DIR \\\n--tpu_name=$TPU_NAME \\\n--tpu_zone=$TPU_ZONE \\\n--gcp_project=$GCP_PROJECT\n```\n\n##### Vizualize model training on Tensorboard\n```bash\ngcloud auth application-default login\n```\n\n```bash\ntensorboard --logdir $MODEL_DIR\n```\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftlatkowski%2Fu-net-tpu","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftlatkowski%2Fu-net-tpu","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftlatkowski%2Fu-net-tpu/lists"}