seems more generic
@@ -39,7 +39,7 @@ class TinyConvNet:
def train(model, optim, steps, BS=128):
losses, accuracies = [], []
- for i in (t := trange(steps, disable=os.getenv('GITHUB_ACTIONS') is not None)):
+ for i in (t := trange(steps, disable=os.getenv('CI') is not None)):
samp = np.random.randint(0, X_train.shape[0], size=(BS))
x = Tensor(X_train[samp].reshape((-1, 28*28)).astype(np.float32))
