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21como-intro-to-deeplearning/README.md

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+# Lecture notes : Introduction to Deep Learning
+
+## Giuseppe Carleo and Filippo Vicentini
+
+Doctoral course at Università degli studi dell'Insubria 
+

21como-intro-to-deeplearning/vae_utils_2.py

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+# Copyright 2021 The Flax Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+    This code is created with reference to torchvision/utils.py.
+
+    Modify: torch.tensor -> jax.numpy.DeviceArray
+
+    If you want to know about this file in detail, please visit the original code:
+        https://github.com/pytorch/vision/blob/master/torchvision/utils.py
+"""
+import math
+from PIL import Image
+
+import jax
+import jax.numpy as jnp
+
+
+def save_image(ndarray, fp, nrow=8, padding=2, pad_value=0.0, format=None):
+    """Make a grid of images and Save it into an image file.
+  Args:
+    ndarray (array_like): 4D mini-batch images of shape (B x H x W x C)
+    fp - A filename(string) or file object
+    nrow (int, optional): Number of images displayed in each row of the grid.
+      The final grid size is ``(B / nrow, nrow)``. Default: ``8``.
+    padding (int, optional): amount of padding. Default: ``2``.
+    scale_each (bool, optional): If ``True``, scale each image in the batch of
+      images separately rather than the (min, max) over all images. Default: ``False``.
+    pad_value (float, optional): Value for the padded pixels. Default: ``0``.
+    format(Optional):  If omitted, the format to use is determined from the filename extension.
+      If a file object was used instead of a filename, this parameter should always be used.
+  """
+    if not (isinstance(ndarray, jnp.ndarray) or
+        (isinstance(ndarray, list) and all(isinstance(t, jnp.ndarray) for t in ndarray))):
+        raise TypeError('array_like of tensors expected, got {}'.format(type(ndarray)))
+
+    ndarray = jnp.asarray(ndarray)
+
+    if ndarray.ndim == 4 and ndarray.shape[-1] == 1:  # single-channel images
+        ndarray = jnp.concatenate((ndarray, ndarray, ndarray), -1)
+
+    # make the mini-batch of images into a grid
+    nmaps = ndarray.shape[0]
+    xmaps = min(nrow, nmaps)
+    ymaps = int(math.ceil(float(nmaps) / xmaps))
+    height, width = int(ndarray.shape[1] + padding), int(ndarray.shape[2] + padding)
+    num_channels = ndarray.shape[3]
+    grid = jnp.full((height * ymaps + padding, width * xmaps + padding, num_channels), pad_value).astype(jnp.float32)
+    k = 0
+    for y in range(ymaps):
+      for x in range(xmaps):
+        if k >= nmaps:
+          break
+        grid = jax.ops.index_update(
+          grid, jax.ops.index[y * height + padding:(y + 1) * height,
+                              x * width + padding:(x + 1) * width],
+          ndarray[k])
+        k = k + 1
+
+    # Add 0.5 after unnormalizing to [0, 255] to round to nearest integer
+    ndarr = jnp.clip(grid * 255.0 + 0.5, 0, 255).astype(jnp.uint8)
+    im = Image.fromarray(ndarr.copy())
+    im.save(fp, format=format)
+
+# Utility functions (don't worry. you don't need to understand this one)
+from matplotlib import pyplot as plt
+
+def show_img(img, ax=None, title=None):
+  """Shows a single image."""
+  if ax is None:
+    ax = plt.gca()
+  ax.imshow(img[..., 0], cmap='gray')
+  ax.set_xticks([])
+  ax.set_yticks([])
+  if title:
+    ax.set_title(title)
+
+def show_img_grid(imgs, titles):
+  """Shows a grid of images."""
+  n = int(np.ceil(len(imgs)**.5))
+  _, axs = plt.subplots(n, n, figsize=(3 * n, 3 * n))
+  for i, (img, title) in enumerate(zip(imgs, titles)):
+    show_img(img, axs[i // n][i % n], title)