diff --git a/lightweight_gan/cli.py b/lightweight_gan/cli.py
index 74c2207..f7f5534 100644
--- a/lightweight_gan/cli.py
+++ b/lightweight_gan/cli.py
@@ -106,6 +106,8 @@ def train_from_folder(
     dataset_aug_prob = 0.,
     multi_gpus = False,
     calculate_fid_every = None,
+    calculate_fid_num_images = 12800,
+    clear_fid_cache = False,
     seed = 42,
     amp = False
 ):
@@ -134,6 +136,8 @@ def train_from_folder(
         aug_types = cast_list(aug_types),
         dataset_aug_prob = dataset_aug_prob,
         calculate_fid_every = calculate_fid_every,
+        calculate_fid_num_images = calculate_fid_num_images,
+        clear_fid_cache = clear_fid_cache,
         amp = amp
     )
 
diff --git a/lightweight_gan/lightweight_gan.py b/lightweight_gan/lightweight_gan.py
index af188f0..59196b5 100644
--- a/lightweight_gan/lightweight_gan.py
+++ b/lightweight_gan/lightweight_gan.py
@@ -43,7 +43,6 @@
 
 NUM_CORES = multiprocessing.cpu_count()
 EXTS = ['jpg', 'jpeg', 'png']
-CALC_FID_NUM_IMAGES = 12800
 
 # helpers
 
@@ -742,6 +741,8 @@ def __init__(
         aug_types = ['translation', 'cutout'],
         dataset_aug_prob = 0.,
         calculate_fid_every = None,
+        calculate_fid_num_images = 12800,
+        clear_fid_cache = False,
         is_ddp = False,
         rank = 0,
         world_size = 1,
@@ -759,6 +760,8 @@ def __init__(
         self.base_dir = base_dir
         self.results_dir = base_dir / results_dir
         self.models_dir = base_dir / models_dir
+        self.fid_dir = base_dir / 'fid' / name
+
         self.config_path = self.models_dir / name / '.config.json'
 
         assert is_power_of_two(image_size), 'image size must be a power of 2 (64, 128, 256, 512, 1024)'
@@ -808,6 +811,8 @@ def __init__(
         self.dataset_aug_prob = dataset_aug_prob
 
         self.calculate_fid_every = calculate_fid_every
+        self.calculate_fid_num_images = calculate_fid_num_images
+        self.clear_fid_cache = clear_fid_cache
 
         self.is_ddp = is_ddp
         self.is_main = rank == 0
@@ -1058,7 +1063,7 @@ def train(self):
                 self.evaluate(floor(self.steps / self.evaluate_every), num_image_tiles = self.num_image_tiles)
 
             if exists(self.calculate_fid_every) and self.steps % self.calculate_fid_every == 0 and self.steps != 0:
-                num_batches = math.ceil(CALC_FID_NUM_IMAGES / self.batch_size)
+                num_batches = math.ceil(self.calculate_fid_num_images / self.batch_size)
                 fid = self.calculate_fid(num_batches)
                 self.last_fid = fid
 
@@ -1126,21 +1131,25 @@ def calculate_fid(self, num_batches):
         from pytorch_fid import fid_score
         torch.cuda.empty_cache()
 
-        real_path = str(self.results_dir / self.name / 'fid_real') + '/'
-        fake_path = str(self.results_dir / self.name / 'fid_fake') + '/'
+        real_path = self.fid_dir / 'real'
+        fake_path = self.fid_dir / 'fake'
 
         # remove any existing files used for fid calculation and recreate directories
-        rmtree(real_path, ignore_errors=True)
-        rmtree(fake_path, ignore_errors=True)
-        os.makedirs(real_path)
-        os.makedirs(fake_path)
+        if not real_path.exists() or self.clear_fid_cache:
+            rmtree(real_path, ignore_errors=True)
+            os.makedirs(real_path)
 
-        for batch_num in tqdm(range(num_batches), desc='calculating FID - saving reals'):
-            real_batch = next(self.loader)
-            for k in range(real_batch.size(0)):
-                torchvision.utils.save_image(real_batch[k, :, :, :], real_path + '{}.png'.format(k + batch_num * self.batch_size))
+            for batch_num in tqdm(range(num_batches), desc='calculating FID - saving reals'):
+                real_batch = next(self.loader)
+                for k, image in enumerate(real_batch.unbind(0)):
+                    ind = k + batch_num * self.batch_size
+                    torchvision.utils.save_image(image, real_path / f'{ind}.png')
 
         # generate a bunch of fake images in results / name / fid_fake
+
+        rmtree(fake_path, ignore_errors=True)
+        os.makedirs(fake_path)
+
         self.GAN.eval()
         ext = self.image_extension
 
@@ -1154,10 +1163,11 @@ def calculate_fid(self, num_batches):
             # moving averages
             generated_images = self.generate_truncated(self.GAN.GE, latents)
 
-            for j in range(generated_images.size(0)):
-                torchvision.utils.save_image(generated_images[j, :, :, :], str(Path(fake_path) / f'{str(j + batch_num * self.batch_size)}-ema.{ext}'))
+            for j, image in enumerate(generated_images.unbind(0)):
+                ind = j + batch_num * self.batch_size
+                torchvision.utils.save_image(image, str(fake_path / f'{str(ind)}-ema.{ext}'))
 
-        return fid_score.calculate_fid_given_paths([real_path, fake_path], 256, latents.device, 2048)
+        return fid_score.calculate_fid_given_paths([str(real_path), str(fake_path)], 256, latents.device, 2048)
 
     @torch.no_grad()
     def generate_truncated(self, G, style, trunc_psi = 0.75, num_image_tiles = 8):
@@ -1224,6 +1234,7 @@ def init_folders(self):
     def clear(self):
         rmtree(str(self.models_dir / self.name), True)
         rmtree(str(self.results_dir / self.name), True)
+        rmtree(str(self.fid_dir), True)
         rmtree(str(self.config_path), True)
         self.init_folders()
 
diff --git a/lightweight_gan/version.py b/lightweight_gan/version.py
index 66e314a..538eb5d 100644
--- a/lightweight_gan/version.py
+++ b/lightweight_gan/version.py
@@ -1 +1 @@
-__version__ = '0.16.3'
+__version__ = '0.16.4'