Skip to content

Commit

Permalink
Fixing PR comments and suggestions
Browse files Browse the repository at this point in the history
  • Loading branch information
@PauAndrio
PauAndrio committed Jun 28, 2024
1 parent b413da0 commit c9460d3
Show file tree
Hide file tree
Showing 11 changed files with 437 additions and 23 deletions.
291 changes: 291 additions & 0 deletions tool_test_output.html
View file

Large diffs are not rendered by default.

101 changes: 101 additions & 0 deletions tool_test_output.json
View file
Original file line number Diff line number Diff line change
@@ -0,0 +1,101 @@
{
"summary": {
"num_errors": 0,
"num_failures": 0,
"num_skips": 0,
"num_tests": 1
},
"tests": [
{
"data": {
"inputs": {
"config_json": {
"id": "8638ae59da399d18",
"src": "hda"
},
"input_train_npy_path": {
"id": "52e55242f7275d02",
"src": "hda"
},
"outname_output_model_pth_path": "output_model.pth",
"outname_output_performance_npz_path": "output_performance.npz",
"outname_output_train_data_npz_path": "output_train_data.npz"
},
"job": {
"command_line": "ln -s /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/files/2/4/5/dataset_245bf14d-1659-4578-a68b-afb1ce9308f1.dat ./input_train_npy_path.npy; ln -s /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/files/2/4/9/dataset_249a96e0-a3d5-42bd-8d9f-8aeb075051f2.dat ./config_json.json; train_mdae --config ./config_json.json --input_train_npy_path ./input_train_npy_path.npy --output_model_pth_path output_model.pth --output_train_data_npz_path output_train_data.npz --output_performance_npz_path output_performance.npz ; mv output_model.pth /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/outputs/dataset_d4a02c99-cb7c-4e22-a5bb-da3d294518d4.dat; if test -f output_train_data.npz; then mv output_train_data.npz /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/outputs/dataset_c853af5a-bc40-41fe-8d2f-8380b5c52aa8.dat; fi; if test -f output_performance.npz; then mv output_performance.npz /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/outputs/dataset_340d714b-ea61-4f02-9a06-3a509f31fc47.dat; fi;",
"command_version": "",
"copied_from_job_id": null,
"create_time": "2024-06-28T09:00:51.154276",
"dependencies": [],
"exit_code": 0,
"external_id": "66123",
"galaxy_version": "24.0",
"handler": null,
"history_id": "52e55242f7275d02",
"id": "63581132e3d3fcd7",
"inputs": {
"config_json": {
"id": "8638ae59da399d18",
"src": "hda",
"uuid": "249a96e0-a3d5-42bd-8d9f-8aeb075051f2"
},
"input_train_npy_path": {
"id": "52e55242f7275d02",
"src": "hda",
"uuid": "245bf14d-1659-4578-a68b-afb1ce9308f1"
}
},
"job_messages": [],
"job_metrics": [],
"job_runner_name": null,
"job_stderr": "",
"job_stdout": "",
"model_class": "Job",
"output_collections": {},
"outputs": {
"output_model_pth_path": {
"id": "63581132e3d3fcd7",
"src": "hda",
"uuid": "d4a02c99-cb7c-4e22-a5bb-da3d294518d4"
},
"output_performance_npz_path": {
"id": "97f585e74de64884",
"src": "hda",
"uuid": "340d714b-ea61-4f02-9a06-3a509f31fc47"
},
"output_train_data_npz_path": {
"id": "3567654777edac40",
"src": "hda",
"uuid": "c853af5a-bc40-41fe-8d2f-8380b5c52aa8"
}
},
"params": {
"__input_ext": "\"npy\"",
"chromInfo": "\"/Users/pau/projects/galaxy/tool-data/shared/ucsc/chrom/?.len\"",
"dbkey": "\"?\"",
"input_model_pth_path": null,
"outname_output_model_pth_path": "\"output_model.pth\"",
"outname_output_performance_npz_path": "\"output_performance.npz\"",
"outname_output_train_data_npz_path": "\"output_train_data.npz\""
},
"state": "ok",
"stderr": "",
"stdout": "2024-06-28 11:00:56,519 [MainThread ] [INFO ] Executing biobb_pytorch.mdae.train_mdae Version: 4.2.1\n2024-06-28 11:00:56,520 [MainThread ] [INFO ] Copy: ./input_train_npy_path.npy to /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a\n2024-06-28 11:00:56,520 [MainThread ] [INFO ] Start Training:\n2024-06-28 11:00:56,521 [MainThread ] [INFO ] Device: cpu\n2024-06-28 11:00:56,521 [MainThread ] [INFO ] Train input file: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/input_train_npy_path.npy\n2024-06-28 11:00:56,521 [MainThread ] [INFO ] File size: 119.66 KB\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Number of atoms: 102\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Number of frames for training: 80 Total number of frames: 100\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Number of epochs: 50\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Partition: 0.8\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Batch size: 1\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Learning rate: 0.0001\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Learning rate step size: 100\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Learning rate gamma: 0.1\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Number of layers: 4\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Input dimensions: 306\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Latent dimensions: 2\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Loss function: MSELoss\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Optimizer: Adam \n2024-06-28 11:00:56,523 [MainThread ] [INFO ] Seed: 1\n2024-06-28 11:00:56,523 [MainThread ] [INFO ] Checkpoint interval: 25\n2024-06-28 11:00:56,523 [MainThread ] [INFO ] Log interval: 10\n\n2024-06-28 11:00:56,871 [MainThread ] [INFO ] Epoch 1/50, Train Loss: 0.042, Validation Loss: 0.040, LR: 0.00010, Duration: 00s, ETA: 17s\n2024-06-28 11:00:56,871 [MainThread ] [INFO ] Saving: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/checkpoint_epoch__0.pth\n2024-06-28 11:00:59,230 [MainThread ] [INFO ] Epoch 11/50, Train Loss: 0.026, Validation Loss: 0.025, LR: 0.00010, Duration: 00s, ETA: 11s\n2024-06-28 11:01:01,832 [MainThread ] [INFO ] Epoch 21/50, Train Loss: 0.024, Validation Loss: 0.024, LR: 0.00010, Duration: 00s, ETA: 07s\n2024-06-28 11:01:03,209 [MainThread ] [INFO ] Saving: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/checkpoint_epoch__25.pth\n2024-06-28 11:01:04,644 [MainThread ] [INFO ] Epoch 31/50, Train Loss: 0.023, Validation Loss: 0.023, LR: 0.00010, Duration: 00s, ETA: 04s\n2024-06-28 11:01:07,345 [MainThread ] [INFO ] Epoch 41/50, Train Loss: 0.023, Validation Loss: 0.023, LR: 0.00010, Duration: 00s, ETA: 02s\n2024-06-28 11:01:09,770 [MainThread ] [INFO ] Epoch 50/50, Train Loss: 0.022, Validation Loss: 0.022, LR: 0.00010, Duration: 00s, ETA: 00s\n2024-06-28 11:01:09,771 [MainThread ] [INFO ] Saving: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/checkpoint_epoch__49.pth\n2024-06-28 11:01:09,775 [MainThread ] [INFO ] End Training, total time: 13s\n2024-06-28 11:01:09,782 [MainThread ] [INFO ] Saving train data to: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/output_train_data.npz\n2024-06-28 11:01:09,782 [MainThread ] [INFO ] File size: 1.31 KB\n2024-06-28 11:01:09,821 [MainThread ] [INFO ] Saving evaluation data to: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/output_performance.npz\n2024-06-28 11:01:09,821 [MainThread ] [INFO ] File size: 121.13 KB\n2024-06-28 11:01:09,825 [MainThread ] [INFO ] Saving best model to: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/output_model.pth\n2024-06-28 11:01:09,826 [MainThread ] [INFO ] Best model epoch: 49\n2024-06-28 11:01:09,826 [MainThread ] [INFO ] File size: 931.57 KB\n2024-06-28 11:01:09,829 [MainThread ] [INFO ] Removed: []\n",
"tool_id": "biobb_pytorch_train_mdae",
"tool_stderr": "",
"tool_stdout": "2024-06-28 11:00:56,519 [MainThread ] [INFO ] Executing biobb_pytorch.mdae.train_mdae Version: 4.2.1\n2024-06-28 11:00:56,520 [MainThread ] [INFO ] Copy: ./input_train_npy_path.npy to /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a\n2024-06-28 11:00:56,520 [MainThread ] [INFO ] Start Training:\n2024-06-28 11:00:56,521 [MainThread ] [INFO ] Device: cpu\n2024-06-28 11:00:56,521 [MainThread ] [INFO ] Train input file: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/input_train_npy_path.npy\n2024-06-28 11:00:56,521 [MainThread ] [INFO ] File size: 119.66 KB\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Number of atoms: 102\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Number of frames for training: 80 Total number of frames: 100\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Number of epochs: 50\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Partition: 0.8\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Batch size: 1\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Learning rate: 0.0001\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Learning rate step size: 100\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Learning rate gamma: 0.1\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Number of layers: 4\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Input dimensions: 306\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Latent dimensions: 2\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Loss function: MSELoss\n2024-06-28 11:00:56,522 [MainThread ] [INFO ] Optimizer: Adam \n2024-06-28 11:00:56,523 [MainThread ] [INFO ] Seed: 1\n2024-06-28 11:00:56,523 [MainThread ] [INFO ] Checkpoint interval: 25\n2024-06-28 11:00:56,523 [MainThread ] [INFO ] Log interval: 10\n\n2024-06-28 11:00:56,871 [MainThread ] [INFO ] Epoch 1/50, Train Loss: 0.042, Validation Loss: 0.040, LR: 0.00010, Duration: 00s, ETA: 17s\n2024-06-28 11:00:56,871 [MainThread ] [INFO ] Saving: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/checkpoint_epoch__0.pth\n2024-06-28 11:00:59,230 [MainThread ] [INFO ] Epoch 11/50, Train Loss: 0.026, Validation Loss: 0.025, LR: 0.00010, Duration: 00s, ETA: 11s\n2024-06-28 11:01:01,832 [MainThread ] [INFO ] Epoch 21/50, Train Loss: 0.024, Validation Loss: 0.024, LR: 0.00010, Duration: 00s, ETA: 07s\n2024-06-28 11:01:03,209 [MainThread ] [INFO ] Saving: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/checkpoint_epoch__25.pth\n2024-06-28 11:01:04,644 [MainThread ] [INFO ] Epoch 31/50, Train Loss: 0.023, Validation Loss: 0.023, LR: 0.00010, Duration: 00s, ETA: 04s\n2024-06-28 11:01:07,345 [MainThread ] [INFO ] Epoch 41/50, Train Loss: 0.023, Validation Loss: 0.023, LR: 0.00010, Duration: 00s, ETA: 02s\n2024-06-28 11:01:09,770 [MainThread ] [INFO ] Epoch 50/50, Train Loss: 0.022, Validation Loss: 0.022, LR: 0.00010, Duration: 00s, ETA: 00s\n2024-06-28 11:01:09,771 [MainThread ] [INFO ] Saving: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/checkpoint_epoch__49.pth\n2024-06-28 11:01:09,775 [MainThread ] [INFO ] End Training, total time: 13s\n2024-06-28 11:01:09,782 [MainThread ] [INFO ] Saving train data to: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/output_train_data.npz\n2024-06-28 11:01:09,782 [MainThread ] [INFO ] File size: 1.31 KB\n2024-06-28 11:01:09,821 [MainThread ] [INFO ] Saving evaluation data to: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/output_performance.npz\n2024-06-28 11:01:09,821 [MainThread ] [INFO ] File size: 121.13 KB\n2024-06-28 11:01:09,825 [MainThread ] [INFO ] Saving best model to: /private/var/folders/yy/x7prx15n63zdp_f5jxc3z6pr0000gn/T/tmpeqf59nxd/job_working_directory/000/3/working/7916b6d5-6698-425a-8aa9-c3c4a359995a/output_model.pth\n2024-06-28 11:01:09,826 [MainThread ] [INFO ] Best model epoch: 49\n2024-06-28 11:01:09,826 [MainThread ] [INFO ] File size: 931.57 KB\n2024-06-28 11:01:09,829 [MainThread ] [INFO ] Removed: []\n",
"update_time": "2024-06-28T09:01:16.128563",
"user_email": "[email protected]"
},
"status": "success",
"test_index": 0,
"time_seconds": 37.86598777770996,
"tool_id": "biobb_pytorch_train_mdae",
"tool_version": "4.2.1"
},
"has_data": true,
"id": "biobb_pytorch_train_mdae-0"
}
],
"version": "0.1"
}
Binary file added tools/biobb_pytorch/.DS_Store
View file
Binary file not shown.
8 changes: 4 additions & 4 deletions tools/biobb_pytorch/.shed.yml
View file
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
name: biobb_pytorch
owner: "Biobb team"
owner: chemteam
description: "biobb_pytorch is the Biobb module collection to create and train ML & DL models using the popular [PyTorch](https://pytorch.org/) Python library."
homepage_url: https://github.com/bioexcel/biobb_pytorch
long_description: |
Expand All @@ -20,6 +20,6 @@ categories:
- Biobb
- Autoencoders
maintainers:
- Pau Andrio
- Genis Bayarri
- Adam Hospital
- PauAndrio
- gbayarri
- adamhospital
25 changes: 18 additions & 7 deletions tools/biobb_pytorch/biobb_apply_mdae.xml
View file
Original file line number Diff line number Diff line change
@@ -1,8 +1,11 @@
<tool id="biobb_pytorch_apply_mdae" name="ApplyMdae" version="4.2.1" >
<tool id="biobb_pytorch_apply_mdae" name="ApplyMdae" version="@TOOL_VERSION@" >
<description>Apply a Molecular Dynamics AutoEncoder (MDAE) PyTorch model.</description>
<macros>
<token name="@TOOL_VERSION@">4.2.1</token>
</macros>

<requirements>
<requirement type="package" version="4.2.1">biobb_pytorch</requirement>
<requirement type="package" version="@TOOL_VERSION@">biobb_pytorch</requirement>
</requirements>

<command detect_errors="exit_code"><![CDATA[
Expand All @@ -15,19 +18,19 @@
apply_mdae
#if str($config_json) != 'None':
#if $config_json:
--config ./config_json.$config_json.ext
#end if
--input_data_npy_path ./input_data_npy_path.$input_data_npy_path.ext
--input_model_pth_path ./input_model_pth_path.$input_model_pth_path.ext
--output_reconstructed_data_npy_path $outname_output_reconstructed_data_npy_path
#if str($outname_output_latent_space_npy_path) != 'None':
#if $outname_output_latent_space_npy_path:
--output_latent_space_npy_path $outname_output_latent_space_npy_path
#end if
;
if test -f $outname_output_reconstructed_data_npy_path; then mv $outname_output_reconstructed_data_npy_path $output_reconstructed_data_npy_path; fi;
mv $outname_output_reconstructed_data_npy_path $output_reconstructed_data_npy_path;
if test -f $outname_output_latent_space_npy_path; then mv $outname_output_latent_space_npy_path $output_latent_space_npy_path; fi;
]]>
Expand All @@ -53,8 +56,16 @@
<param name="input_model_pth_path" value="ref_output_model.pth" />
<param name="outname_output_reconstructed_data_npy_path" value="output_reconstructed_data.npy" />
<param name="outname_output_latent_space_npy_path" value="output_latent_space.npy" />
<output name="output_reconstructed_data_npy_path" file="ref_output_reconstructed_data.npy" compare="sim_size" />
<output name="output_latent_space_npy_path" file="ref_output_latent_space.npy" compare="sim_size" />
<output name="output_reconstructed_data_npy_path" ftype="npy">
<assert_contents>
<has_size value="123k" delta="50k"/>
</assert_contents>
</output>
<output name="output_latent_space_npy_path" ftype="npy">
<assert_contents>
<has_size value="928" delta="200"/>
</assert_contents>
</output>
</test>
</tests>

Expand Down
Loading

0 comments on commit c9460d3

Please sign in to comment.