diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..eede66d83f98ba9915ece45358a792562b5aedab
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+*.pt
\ No newline at end of file
diff --git a/Logs/job_error_10022299.log b/Logs/job_error_10022299.log
new file mode 100644
index 0000000000000000000000000000000000000000..91c131f3170975f8d8edf77755ee3f96f2646c44
Binary files /dev/null and b/Logs/job_error_10022299.log differ
diff --git a/Logs/job_error_10022300 b/Logs/job_error_10022300
new file mode 100644
index 0000000000000000000000000000000000000000..784e3b31d77a335c11ee8ffde96562564adeb8e1
Binary files /dev/null and b/Logs/job_error_10022300 differ
diff --git a/Logs/job_error_10022301.log b/Logs/job_error_10022301.log
new file mode 100644
index 0000000000000000000000000000000000000000..144bc17703a08add8388e193b59ae232ca223114
Binary files /dev/null and b/Logs/job_error_10022301.log differ
diff --git a/Logs/job_error_10022302.log b/Logs/job_error_10022302.log
new file mode 100644
index 0000000000000000000000000000000000000000..d31414d71d2b9e62d2b26e593a6a58b1c4c8fd9e
Binary files /dev/null and b/Logs/job_error_10022302.log differ
diff --git a/Logs/job_output_10022299.log b/Logs/job_output_10022299.log
new file mode 100644
index 0000000000000000000000000000000000000000..b88775bf8f7ad069c926ebadea5eca5fccb5cb1e
--- /dev/null
+++ b/Logs/job_output_10022299.log
@@ -0,0 +1,37 @@
+The activation script must be sourced, otherwise the virtual environment will not work.
+Setting vars
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: No model milestone found, restarting training
+0: No model milestone found, restarting training
+0: No model milestone found, restarting training
+3: No model milestone found, restarting training
+3: No model milestone found, restarting training
+3: No model milestone found, restarting training
+1: No model milestone found, restarting training
+3: No model milestone found, restarting training
+1: No model milestone found, restarting training
+1: No model milestone found, restarting training
+1: No model milestone found, restarting training
+2: No model milestone found, restarting training
+2: No model milestone found, restarting training
+2: No model milestone found, restarting training
+2: No model milestone found, restarting training
+0: No model milestone found, restarting training
+0: Dataset stats loaded from disk.
+0: Stacking Inception features for 50000 generated samples.
+0: fid_score: 439.4099380441412
diff --git a/Logs/job_output_10022300.log b/Logs/job_output_10022300.log
new file mode 100644
index 0000000000000000000000000000000000000000..3814a4bd07dbe1ec7cd7a19191b08aaf4f9da71e
--- /dev/null
+++ b/Logs/job_output_10022300.log
@@ -0,0 +1,69 @@
+The activation script must be sourced, otherwise the virtual environment will not work.
+Setting vars
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Loading 1
+0: Loading 1
+0: Loading 1
+1: Loading 1Loading 1
+1: 
+1: Loading 1
+1: Loading 1
+2: Loading 1
+2: Loading 1
+2: Loading 1
+2: Loading 1
+3: Loading 1
+3: Loading 1
+3: Loading 1
+3: Loading 1
+0: Loading 1
+2: loading from version 2.0.12
+3: loading from version 2.0.12
+2: loading from version 2.0.12
+2: Loaded 1, continuing training
+3: Loaded 1, continuing training
+1: loading from version 2.0.12
+3: loading from version 2.0.12
+0: loading from version 2.0.12
+0: loading from version 2.0.12
+3: loading from version 2.0.12
+1: loading from version 2.0.12
+2: Loaded 1, continuing training
+0: loading from version 2.0.12
+0: Loaded 1, continuing training
+1: Loaded 1, continuing training
+0: Loaded 1, continuing training
+3: Loaded 1, continuing training
+3: Loaded 1, continuing training
+1: Loaded 1, continuing training
+2: loading from version 2.0.12
+3: loading from version 2.0.12
+1: loading from version 2.0.12
+0: Loaded 1, continuing training
+1: loading from version 2.0.12
+2: Loaded 1, continuing training
+1: Loaded 1, continuing training
+3: Loaded 1, continuing training
+2: loading from version 2.0.12
+1: Loaded 1, continuing training
+2: Loaded 1, continuing training
+0: loading from version 2.0.12
+0: Loaded 1, continuing training
+0: Dataset stats loaded from disk.
+0: Stacking Inception features for 50000 generated samples.
+0: fid_score: 438.8738471630822
diff --git a/Logs/job_output_10022301.log b/Logs/job_output_10022301.log
new file mode 100644
index 0000000000000000000000000000000000000000..6b2890b3d4cfe2a19e92ca00f2593ffb0b7c932f
--- /dev/null
+++ b/Logs/job_output_10022301.log
@@ -0,0 +1,69 @@
+The activation script must be sourced, otherwise the virtual environment will not work.
+Setting vars
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Loading 2
+0: Loading 2
+0: Loading 2
+1: Loading 2
+1: Loading 2
+1: Loading 2
+1: Loading 2
+2: Loading 2
+2: Loading 2Loading 2
+2: 
+2: Loading 2
+3: Loading 2
+3: Loading 2
+3: Loading 2
+3: Loading 2
+0: Loading 2
+0: loading from version 2.0.12
+0: loading from version 2.0.12
+0: loading from version 2.0.12
+0: Loaded 2, continuing training
+0: Loaded 2, continuing training
+0: Loaded 2, continuing training
+0: loading from version 2.0.12
+0: Loaded 2, continuing training
+2: loading from version 2.0.12
+2: loading from version 2.0.12
+2: loading from version 2.0.12
+2: loading from version 2.0.12
+2: Loaded 2, continuing training
+2: Loaded 2, continuing training
+2: Loaded 2, continuing training
+2: Loaded 2, continuing training
+3: loading from version 2.0.12
+3: loading from version 2.0.12
+3: Loaded 2, continuing training
+3: Loaded 2, continuing training
+3: loading from version 2.0.12
+3: loading from version 2.0.12
+3: Loaded 2, continuing training
+3: Loaded 2, continuing training
+1: loading from version 2.0.12
+1: loading from version 2.0.12
+1: loading from version 2.0.12
+1: loading from version 2.0.12
+1: Loaded 2, continuing training
+1: Loaded 2, continuing training
+1: Loaded 2, continuing training
+1: Loaded 2, continuing training
+0: Dataset stats loaded from disk.
+0: Stacking Inception features for 50000 generated samples.
+0: fid_score: 364.6970712719158
diff --git a/Logs/job_output_10022302.log b/Logs/job_output_10022302.log
new file mode 100644
index 0000000000000000000000000000000000000000..71bf02123d3f58c37d6a49f9b58a0215607cfced
--- /dev/null
+++ b/Logs/job_output_10022302.log
@@ -0,0 +1,69 @@
+The activation script must be sourced, otherwise the virtual environment will not work.
+Setting vars
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+2: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+1: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+3: Non-A100 GPU detected, using math or mem efficient attention if input tensor is on cuda
+0: Loading 3
+0: Loading 3
+2: Loading 3
+1: Loading 3
+0: Loading 3
+2: Loading 3
+2: Loading 3
+1: Loading 3
+1: Loading 3
+2: Loading 3
+3: Loading 3
+3: Loading 3
+3: Loading 3
+3: Loading 3
+1: Loading 3
+0: loading from version 2.0.12
+0: Loaded 3, continuing training
+0: loading from version 2.0.12
+0: Loaded 3, continuing training
+0: loading from version 2.0.12
+0: Loaded 3, continuing training
+3: loading from version 2.0.12
+3: loading from version 2.0.12Loaded 3, continuing training
+3: 
+3: Loaded 3, continuing training
+3: loading from version 2.0.12
+3: loading from version 2.0.12
+3: Loaded 3, continuing training
+3: Loaded 3, continuing training
+1: loading from version 2.0.12
+1: Loaded 3, continuing training
+1: loading from version 2.0.12
+1: Loaded 3, continuing training
+1: loading from version 2.0.12
+1: Loaded 3, continuing training
+1: loading from version 2.0.12
+1: Loaded 3, continuing training
+0: Loading 3
+2: loading from version 2.0.12
+2: Loaded 3, continuing training
+2: loading from version 2.0.12
+2: Loaded 3, continuing training
+2: loading from version 2.0.12
+2: Loaded 3, continuing training
+2: loading from version 2.0.12
+2: Loaded 3, continuing training
+0: loading from version 2.0.12
+0: Loaded 3, continuing training
+0: Dataset stats loaded from disk.
+0: Stacking Inception features for 50000 generated samples.
+0: fid_score: 263.1563520569741
diff --git a/README.md b/README.md
index 1b58b843dbeeee4819601d4dbaa36a38b6f8575f..06e3f1accd1c355a4fc94e0b8c38f2228e956189 100644
--- a/README.md
+++ b/README.md
@@ -1,93 +1,8 @@
-# DistribDiffusion
+# Distributed Denoising Diffusion
 
+## Dependecies
 
-
-## Getting started
-
-To make it easy for you to get started with GitLab, here's a list of recommended next steps.
-
-Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
-
-## Add your files
-
-- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
-- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
-
-```
-cd existing_repo
-git remote add origin https://gitlab.jsc.fz-juelich.de/vasireddy1/DistribDiffusion.git
-git branch -M main
-git push -uf origin main
-```
-
-## Integrate with your tools
-
-- [ ] [Set up project integrations](https://gitlab.jsc.fz-juelich.de/vasireddy1/DistribDiffusion/-/settings/integrations)
-
-## Collaborate with your team
-
-- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
-- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
-- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
-- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
-- [ ] [Set auto-merge](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
-
-## Test and Deploy
-
-Use the built-in continuous integration in GitLab.
-
-- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
-- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing (SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
-- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
-- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
-- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
-
-***
-
-# Editing this README
-
-When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thanks to [makeareadme.com](https://www.makeareadme.com/) for this template.
-
-## Suggestions for a good README
-
-Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
-
-## Name
-Choose a self-explaining name for your project.
-
-## Description
-Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
-
-## Badges
-On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
-
-## Visuals
-Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
-
-## Installation
-Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
-
-## Usage
-Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
-
-## Support
-Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
-
-## Roadmap
-If you have ideas for releases in the future, it is a good idea to list them in the README.
-
-## Contributing
-State if you are open to contributions and what your requirements are for accepting them.
-
-For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
-
-You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
-
-## Authors and acknowledgment
-Show your appreciation to those who have contributed to the project.
-
-## License
-For open source projects, say how it is licensed.
-
-## Project status
-If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
+```bash
+pip install denoising_diffusion_pytorch
+pip install accelerate
+```
\ No newline at end of file
diff --git a/dataInfer.py b/dataInfer.py
new file mode 100644
index 0000000000000000000000000000000000000000..39b8f312e672fab3f9b769ecaab60053ba8f7977
--- /dev/null
+++ b/dataInfer.py
@@ -0,0 +1,47 @@
+from accelerate import Accelerator
+import torch
+import os
+import re
+import torch.distributed as dist
+from denoising_diffusion_pytorch import Unet, GaussianDiffusion, Trainer
+import torch._dynamo
+from datetime import timedelta
+
+torch._dynamo.config.suppress_errors = True
+dist.init_process_group(backend='nccl',init_method='env://',timeout=timedelta(minutes=60))
+
+model = Unet(
+    dim = 64,
+    dim_mults = (1, 2, 4, 8),
+    flash_attn = True
+)
+
+diffusion = GaussianDiffusion(
+    model,
+    image_size = 128,
+    timesteps = 1000,           
+    sampling_timesteps = 250    
+)
+
+trainer = Trainer(
+    diffusion,
+    '/p/project1/deepacf/intelliaq/vasireddy1/Diffusion/lucidrains/Training/Female', # Add your training image path 
+    train_batch_size = 32,
+    train_lr = 8e-5,
+    train_num_steps = 700000,         
+    gradient_accumulate_every = 2,    
+    ema_decay = 0.995,                
+    amp = True,                       # turn on mixed precision
+    calculate_fid = True,              
+    num_workers = 24,                  # number of workers for dataloader manually included in the trainer constructor
+)
+
+milestone_latest =max((int(re.search(r'\d+', f).group()) for f in os.listdir("./results") if re.match(r'model-\d+\.pt', f)), default=None); 
+if milestone_latest is not None:
+    print(f"Loading {milestone_latest}")
+    trainer.load(milestone_latest)
+    print(f"Loaded {milestone_latest}, continuing training")
+else:
+    print("No model milestone found, restarting training")
+    
+trainer.train()
diff --git a/dataInfer.sh b/dataInfer.sh
new file mode 100644
index 0000000000000000000000000000000000000000..9dcf1f95fcc036347d1a9ff5a689535418d0ae01
--- /dev/null
+++ b/dataInfer.sh
@@ -0,0 +1,64 @@
+#!/bin/bash
+#SBATCH --job-name=inferAccelerate  # Job name
+#SBATCH --partition=booster         # Partition name
+#SBATCH --ntasks=4                  # Number of tasks per node (1 per GPU)
+#SBATCH --ntasks-per-node=4         # Number of MPI ranks per node
+#SBATCH --cpus-per-task=24          # Number of CPU cores per task
+#SBATCH --account=deepacf           # Account name
+#SBATCH --gres=gpu:4                # Request 4 GPUs
+#SBATCH --output=job_output_%j.log  # Output file (%j is replaced by the job ID)
+#SBATCH --error=job_error_%j.log    # Error file (%j is replaced by the job ID)
+#SBATCH --time=12:00:00             # Total run time limit (HH:MM:SS)
+
+export CUDA_MPS_PIPE_DIRECTORY=/tmp/mps_$SLURM_JOB_ID
+export CUDA_MPS_LOG_DIRECTORY=/tmp/mps_logs_$SLURM_JOB_ID
+nvidia-cuda-mps-control -d
+
+export NCCL_DEBUG=DEBUG                 # better with info level once debug is sorted
+export NCCL_IB_TIMEOUT=22
+export NCCL_IB_DISABLE=1
+export NCCL_SOCKET_IFNAME=^docker0,lo
+export NCCL_NET_GDR_LEVEL=PHB
+export NCCL_TIMEOUT=3600                # 1 hour since lesser was timing out workers for this task
+
+export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK
+export CUDA_LAUNCH_BLOCKING=1
+export CUDA_VISIBLE_DEVICES=0,1,2,3
+
+export SRUN_CPUS_PER_TASK="$SLURM_CPUS_PER_TASK" # Without this, srun does not inherit cpus-per-task from sbatch.
+export GPUS_PER_NODE=4
+
+export MASTER_ADDR="$(nslookup "$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1)i" | grep -oP '(?<=Address: ).*')"
+export MASTER_PORT=51409
+
+export TORCH_LOGS="+dynamo"
+export TORCHDYNAMO_VERBOSE=1
+
+source /p/project1/deepacf/intelliaq/vasireddy1/clean_venv/sc_venv_template/activate.sh
+
+srun -v -l accelerate launch \
+    --mixed_precision 'fp16' \
+    --num_machines=$SLURM_JOB_NUM_NODES \
+    --machine_rank=$SLURM_NODEID \
+    --rdzv_backend c10d \
+    --multi_gpu \
+    --num_processes=$(($SLURM_JOB_NUM_NODES * $GPUS_PER_NODE)) \
+    --dynamo_backend 'cudagraphs' \
+    --main_process_ip $MASTER_ADDR \
+    --main_process_port $MASTER_PORT \
+    dataInfer.py
+
+# # Run the application with mpirun
+# mpirun -np $(($SLURM_JOB_NUM_NODES * $SLURM_NTASKS_PER_NODE)) \
+#        --bind-to none \
+#        --map-by slot \
+#        -x NCCL_DEBUG=$NCCL_DEBUG \
+#        -x NCCL_SOCKET_IFNAME=$NCCL_SOCKET_IFNAME \
+#        -x NCCL_IB_DISABLE=$NCCL_IB_DISABLE \
+#        -x NCCL_TIMEOUT=$NCCL_TIMEOUT \
+#        -x CUDA_LAUNCH_BLOCKING=$CUDA_LAUNCH_BLOCKING \
+#        -x CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES \
+#        -x OMP_NUM_THREADS=$OMP_NUM_THREADS \
+#        python dataInfer.py
+
+nvidia-cuda-mps-control -s
\ No newline at end of file
diff --git a/dependencyseq.txt b/dependencyseq.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6537d4c14ce4c6374879e11044f8dfa8b2d8c2aa
--- /dev/null
+++ b/dependencyseq.txt
@@ -0,0 +1,8 @@
+sbatch --dependency=afterok:10017584 --time=24:00:00 dataInfer.sh
+sbatch --dependency=afterok:10019488 --time=24:00:00 dataInfer.sh
+sbatch --dependency=afterok:10022059 --time=24:00:00 dataInfer.sh #10022060
+
+## Accelerated
+sbatch --dependency=afterok:10022299 --time=24:00:00 dataInfer.sh
+sbatch --dependency=afterok:10022300 --time=24:00:00 dataInfer.sh
+sbatch --dependency=afterok:10022301 --time=24:00:00 dataInfer.sh #10022302
diff --git a/results/.ipynb_checkpoints/sample-1-checkpoint.png b/results/.ipynb_checkpoints/sample-1-checkpoint.png
new file mode 100644
index 0000000000000000000000000000000000000000..a4de89df7f9ee5d9f6c45c355d9b5ea57bf96268
Binary files /dev/null and b/results/.ipynb_checkpoints/sample-1-checkpoint.png differ
diff --git a/results/.ipynb_checkpoints/sample-2-checkpoint.png b/results/.ipynb_checkpoints/sample-2-checkpoint.png
new file mode 100644
index 0000000000000000000000000000000000000000..6b477d1d1561b88f86b417c243cf9de237fabc04
Binary files /dev/null and b/results/.ipynb_checkpoints/sample-2-checkpoint.png differ
diff --git a/results/.ipynb_checkpoints/sample-4-checkpoint.png b/results/.ipynb_checkpoints/sample-4-checkpoint.png
new file mode 100644
index 0000000000000000000000000000000000000000..d21f265c9740f2507cd6b64e73a46eb3538c6cfe
Binary files /dev/null and b/results/.ipynb_checkpoints/sample-4-checkpoint.png differ
diff --git a/results/dataset_stats.npz b/results/dataset_stats.npz
new file mode 100644
index 0000000000000000000000000000000000000000..ab381daec3ffe21693927ed8eebf63193968d7e8
Binary files /dev/null and b/results/dataset_stats.npz differ
diff --git a/results/sample-1.png b/results/sample-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..a4de89df7f9ee5d9f6c45c355d9b5ea57bf96268
Binary files /dev/null and b/results/sample-1.png differ
diff --git a/results/sample-2.png b/results/sample-2.png
new file mode 100644
index 0000000000000000000000000000000000000000..6b477d1d1561b88f86b417c243cf9de237fabc04
Binary files /dev/null and b/results/sample-2.png differ
diff --git a/results/sample-3.png b/results/sample-3.png
new file mode 100644
index 0000000000000000000000000000000000000000..c2142fc622d2031ace5e3dc896fa83b5140ec7c5
Binary files /dev/null and b/results/sample-3.png differ
diff --git a/results/sample-4.png b/results/sample-4.png
new file mode 100644
index 0000000000000000000000000000000000000000..d21f265c9740f2507cd6b64e73a46eb3538c6cfe
Binary files /dev/null and b/results/sample-4.png differ
diff --git a/results/sample-5.png b/results/sample-5.png
new file mode 100644
index 0000000000000000000000000000000000000000..0df66a44fc1234dbf2663afb01288cd910174614
Binary files /dev/null and b/results/sample-5.png differ