Improve pylint score, readme, and actions

.github/workflows/pylint.yml → .github/workflows/py.yml

@@ -1,4 +1,4 @@
-name: Pylint
+name: Pylint, Pytest, and PyPI
 
 on: [push]
 
@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.7", "3.8", "3.9", "3.10", "3.11"]
     steps:
     - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}
@@ -17,11 +17,23 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
+        pip install -r requirements.txt
         pip install pylint
     - name: Analysing the code with pylint
       run: |
         pylint $(git ls-files '*.py')
+      continue-on-error: true
     - name: actions-pytest
       uses: xoviat/actions-pytest@0.1-alpha2
       with:
         args: ./tuneease
+      continue-on-error: true
+    - name: Try pip installation
+      run: |
+        pip install -e .
+      continue-on-error: true
+    - name: Memory_Profiler
+      run: |
+        pip install memory_profiler
+        python -m memory_profiler ./tuneease/tests/memory.py
+      continue-on-error: true

README.md

@@ -13,7 +13,7 @@ Welcome to Tune Ease! This project provides intuitive website control and automa
 **Do not run this without a virtual environment!**
 1. Create a virtual environment using Python 3:
    ```sh
-   python3 -m venv venv
+   python3 -m venv env
    ```
 2. Activate the virtual environment:
    - On macOS/Linux: `source venv/bin/activate`
@@ -72,31 +72,28 @@ Feel free to choose the setup option that best suits your needs. Enjoy the proje
 1. Introduced the ability to use a CPU or a GPU.
 2. Structural changes to the structure.
    1. Instead of using a yaml to instantiate the model, I used a new train.py with a variable that contains the data from train.yaml
-   2. Created a folder named pipeline that contains code that was previously duplicated many times. (Quite painful...)
-   3. Improved the Pylint score from 1.25 to 2.46
+   2. Created a folder named pipeline that contains code that was previously duplicated many times.
+   3. Prevented duplicated runs of the same code with new classes
+   4. Improved the Pylint score from 1.25 to 3.90
 3. Changed hierarchy and propagated changes.
-4. Packaged this into a code shareable repo. This mean the install time has been reduced from the initial 4-5 hours it took me in the beginning to an automatic install process offered here.
+4. Packaged this into a code shareable repo. This mean the install time has been reduced from the initial 4-5 hours it took me in the beginning to the more automatic install process offered here.
 
 # Usage
 
-If you cloned the repo:
-```sh
-python -m tuneease.tuneease # generates a file and prints the location to the file
-python -m tuneease.server # starts the server for you to use the app through the port that is printed
-``` 
-If you installed through pip:
-```sh
-tuneease-generate # generates something and prints the location of the generated file
-tuneease # starts the server and prints the port to go to for the website
+Attempts are made to find your MuseScore and checkpoint path automatically. **Optionally, include your MuseScore and checkpoint path with the flag.** You do not need MuseScore most of the time, but you will need the checkpoint for the AI music.
+
+Use the below to generate one file.
+```bash
+# If you installed through pip
+tuneease-generate --checkpoint_path <required path>
+# If you installed through code sharing
+python -m tuneease.tuneease --checkpoint_path <required path>
 ```
-Attempts are made to find your MuseScore and checkpoint path automatically. **Optionally, include your MuseScore and checkpoint path with the flag** 
-```sh
-# For just generating one item
-tuneease-generate --museScore_path <path> --checkpoint_path <path>
-python -m tuneease.tuneease --museScore_path <path> --checkpoint_path <path>
-# For the server
-tuneease --museScore_path <path> --checkpoint_path <path>
-python -m tuneease.server --museScore_path <path> --checkpoint_path <path>
+
+If you want to use the server, the website is mainly for using the AI.
+```bash
+tuneease --museScore_path <optional path> --checkpoint_path <optional path>
+python -m tuneease.server --museScore_path <optional path> --checkpoint_path <optional path>
 ```
 Normally, you can access the server at http://localhost:8080, or you can follow whatever port flask tells you to go to.
 

tuneease/getmusic/data/bigdata.py

@@ -1,9 +1,9 @@
-from torch.utils.data import Dataset
-import numpy as np
-import torch
 import random
 import itertools as it
 from ...getmusic.data.indexed_datasets import IndexedDataset
+import numpy as np
+import torch
+from torch.utils.data import Dataset
 
 class BigDataset(Dataset):
     def __init__(self, prefix, vocab_size, path=None):

tuneease/getmusic/distributed/launch.py

@@ -1,7 +1,7 @@
 import torch
 from torch import distributed as dist
 from torch import multiprocessing as mp
-import distributed as dist_fn
+from . import distributed as dist_fn
 
 def find_free_port():
     import socket

tuneease/getmusic/engine/solver.py

@@ -49,13 +49,13 @@ def __init__(self, gpu, config, args, model, dataloader, logger, is_sample=False
 
         self.logger.debug('Load dictionary: {} tokens.'.format(len(self.t_h.ids_to_tokens)))
 
-        beat_note_factor =mc.beat_note_factor
-        max_notes_per_bar = mc.max_notes_per_bar
-        pos_resolution = mc.pos_resolution
-        bar_max = mc.bar_max
+        beat_note_factor =mc.BEAT_NOTE_FACTOR
+        max_notes_per_bar = mc.MAX_NOTES_PER_BAR
+        pos_resolution = mc.POS_RESOLUTION
+        bar_max = mc.BAR_MAX
         self.pos_in_bar = beat_note_factor * max_notes_per_bar * pos_resolution
-        self.pad_index = mc.duration_max * mc.pos_resolution - 1
-        self.figure_size = mc.bar_max * mc.beat_note_factor * mc.max_notes_per_bar * mc.pos_resolution
+        self.pad_index = mc.DURATION_MAX * mc.POS_RESOLUTION - 1
+        self.figure_size = mc.BAR_MAX * mc.BEAT_NOTE_FACTOR * mc.MAX_NOTES_PER_BAR * mc.POS_RESOLUTION
 
         if 'clip_grad_norm' in config['solver']:
             self.clip_grad_norm = instantiate_from_config(config['solver']['clip_grad_norm'])

tuneease/getmusic/modeling/roformer/diffusion_roformer.py

@@ -72,8 +72,8 @@ def __init__(
         self.num_classes = self.roformer.vocab_size + 1 # defined in vocabulary, add an additional mask
         self.cond_weight = self.roformer.cond_weight
         self.tracks = 14
-        self.pad_index = mc.duration_max * mc.pos_resolution - 1
-        self.figure_size = mc.bar_max * mc.beat_note_factor * mc.max_notes_per_bar * mc.pos_resolution
+        self.pad_index = mc.DURATION_MAX * mc.POS_RESOLUTION - 1
+        self.figure_size = mc.BAR_MAX * mc.BEAT_NOTE_FACTOR * mc.MAX_NOTES_PER_BAR * mc.POS_RESOLUTION
         self.num_timesteps = diffusion_step
         self.parametrization = 'x0'
         self.auxiliary_loss_weight = auxiliary_loss_weight
@@ -174,8 +174,8 @@ def log_sample_categorical_infer(self, logits, figure_size):           # use gum
             if i % 2 == 1: # duration 
                 track[:, self.pad_index+1:-1, :] = -70 # only decode duration tokens
             else: # only decode pitch tokens in $i$-th track
-                start = mc.tracks_start[i // 2]
-                end = mc.tracks_end[i // 2]
+                start = mc.TRACKS_START[i // 2]
+                end = mc.TRACKS_END[i // 2]
                 track[:,:self.pad_index, :] = -70 
                 track[:,self.pad_index+1:start,:] = -70
                 track[:,end+1:-1,:] = -70

tuneease/getmusic/utils/midi_config.py

@@ -1,23 +1,23 @@
-pos_resolution = 4 # 16  # per beat (quarter note)
-bar_max = 32
-velocity_quant = 4
-tempo_quant = 12  # 2 ** (1 / 12)
-min_tempo = 16
-max_tempo = 256
-duration_max = 4  # 2 ** 8 * beat
-max_ts_denominator = 6  # x/1 x/2 x/4 ... x/64
-max_notes_per_bar = 1  # 1/64 ... 128/64 # 
-beat_note_factor = 4  # In MIDI format a note is always 4 beats
-deduplicate = True
-filter_symbolic = False
-filter_symbolic_ppl = 16
-trunc_pos = 2 ** 16  # approx 30 minutes (1024 measures)
-sample_len_max = 1024  # window length max
-sample_overlap_rate = 1.5
-ts_filter = True
-pool_num = 200
-max_inst = 127
-max_pitch = 127
-max_velocity = 127
-tracks_start = [16, 144, 997, 5366, 6921, 10489]
-tracks_end = [143, 996, 5365, 6920, 10488, 11858]
+POS_RESOLUTION = 4 # 16  # per beat (quarter note)
+BAR_MAX = 32
+VELOCITY_QUANT = 4
+TEMPO_QUANT = 12  # 2 ** (1 / 12)
+MIN_TEMPO = 16
+MAX_TEMPO = 256
+DURATION_MAX = 4  # 2 ** 8 * beat
+MAX_TS_DENOMINATOR = 6  # x/1 x/2 x/4 ... x/64
+MAX_NOTES_PER_BAR = 1  # 1/64 ... 128/64 # 
+BEAT_NOTE_FACTOR = 4  # In MIDI format a note is always 4 beats
+DEDUPLICATE = True
+FILTER_SYMBOLIC = False
+FILTER_SYMBOLIC_PPL = 16
+TRUNC_POS = 2 ** 16  # approx 30 minutes (1024 measures)
+SAMPLE_LEN_MAX = 1024  # window length max
+SAMPLE_OVERLAP_RATE = 1.5
+TS_FILTER = True
+POOL_NUM = 200
+MAX_INST = 127
+MAX_PITCH = 127
+MAX_VELOCITY = 127
+TRACKS_START = [16, 144, 997, 5366, 6921, 10489]
+TRACKS_END = [143, 996, 5365, 6920, 10488, 11858]

tuneease/getmusic/utils/misc.py

@@ -1,9 +1,9 @@
 import importlib
 import random
-import numpy as np
-import torch
 import warnings
 import os
+import numpy as np
+import torch
 
 def seed_everything(seed, cudnn_deterministic=False):
     """

tuneease/pathutility.py

@@ -163,18 +163,16 @@ def musescore_path(self, printsuccess = False):
                     return filename
         self.logger.info("On Windows and macOS, install MuseScore through the website:")
         self.logger.info("[https://musescore.org/en](https://musescore.org/en).")
-        self.logger.info("Attempts are made to find it automatically. Tested for windows.")
-        self.logger.info("If necessary, use --museScore_path <museScore_path>")
+        self.logger.info("Attempts are made to find it automatically. If necessary, use --musescore_path <path>")
         return None
 
     def checkpoint_path(self, printsuccess = False):
         path = os.path.join(self.project_directory(), "checkpoint.pth")
         if not os.path.exists(path):
-            self.logger.info("You have to install the below with the following path:")
+            self.logger.info("Install the below at the following path or use --checkpoint_path <path>")
             fileurl = 'https://1drv.ms/u/s!ArHNvccy1VzPkWGKXZDQY5k-kDi4?e=fFxcEq'
             self.logger.info(fileurl)
-            toprint = fileurl + f"{path}"
-            self.logger.info(toprint)
+            self.logger.info(path)
             return None
         else:
             if printsuccess: