organization cleanup

README.md

@@ -1,9 +1,9 @@
 # Deep Convolution Audio Generation (WIP)
 
-Implementing Deep Convolution to generate audio using generative and autoencoding networks
+Implementing Deep Convolution to generate audio using a generative network
 
 ## Directories
 
-- `model`: Model save and generated output location
-- `src`: Source code for models
+- `model`: Trained model and generated audio
+- `src`: Model source code
   - `utils`: Model and data utilities

src/dcgan_architecture.py → src/architecture.py

@@ -1,7 +1,5 @@
 import torch
 import torch.nn as nn
-
-# sys.path.append("../utils") # get this working & fix file structure
 from utils.helpers import N_CHANNELS, N_FRAMES, N_FREQ_BINS
 
 # Constants Constants

src/dcgan.py

@@ -3,12 +3,12 @@
 import torch.optim as optim
 from torch.utils.data import DataLoader, TensorDataset, random_split
 
-from dcgan_architecture import (
+from architecture import (
     BATCH_SIZE,
     Discriminator,
     Generator,
 )
-from dcgan_train import training_loop
+from train import training_loop
 from utils.helpers import (
     compiled_data_path,
     get_device,

src/dcgan_generate.py → src/generate.py

@@ -1,5 +1,5 @@
 import torch
-from dcgan_architecture import Generator, LATENT_DIM
+from architecture import Generator, LATENT_DIM
 from utils.helpers import amplitudes_to_wav, get_device, graph_spectrogram
 
 # Initialize Generator

src/dcgan_train.py → src/train.py

@@ -1,7 +1,6 @@
 import torch
-
+from architecture import LATENT_DIM
 from utils.helpers import save_model
-from dcgan_architecture import LATENT_DIM
 
 
 N_EPOCHS = 10

src/utils/helpers.py

@@ -1,10 +1,10 @@
-import os
 import librosa
-import scipy
-import soundfile as sf
 import numpy as np
+import os
 import plotly.graph_objects as go
 import plotly.subplots as sp
+import scipy
+import soundfile as sf
 import torch
 
 # Constants