Try something tricky from the PySoundfile source to get docs to build…

… without libsndfile installed

docs/source/conf.py

@@ -12,13 +12,13 @@
 # All configuration values have a default; values that are commented out
 # serve to show the default.
 
-import sys
 import os
-import shlex
+import sys
 
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the
 # documentation root, use os.path.abspath to make it absolute, like shown here.
+sys.path.insert(0, '.')
 sys.path.insert(0, os.path.abspath('../../'))
 
 # -- General configuration ------------------------------------------------
@@ -292,3 +292,7 @@
 
 # If true, do not generate a @detailmenu in the "Top" node's menu.
 #texinfo_no_detailmenu = False
+
+# Fake imports
+import fake_cffi
+sys.modules['cffi'] = sys.modules['fake_cffi']

docs/source/fake_cffi.py

@@ -0,0 +1,15 @@
+class FFI(object):
+
+    def cdef(self, _):
+        pass
+
+    def dlopen(self, _):
+        return self
+
+    def string(self, _):
+        return b'not implemented'
+
+    def sf_version_string(self):
+        return NotImplemented
+
+    SFC_GET_FORMAT_INFO = NotImplemented

zounds/learn/gan_trainer.py

@@ -26,10 +26,13 @@ def train(self, data, epochs, batch_size):
         data = data.astype(np.float32)
 
         zdim = self.latent_dimension
+
         # TODO: These dimensions work for vanilla GANs, but need to be
         # reversed (batch_size, zdim, 1) for convolutional GANs
-        noise = torch.FloatTensor(batch_size, 1, zdim)
-        fixed_noise = torch.FloatTensor(batch_size, 1, zdim).normal_(0, 1)
+
+        noise_shape = (batch_size,) + self.latent_dimension
+        noise = torch.FloatTensor(*noise_shape)
+        fixed_noise = torch.FloatTensor(*noise_shape).normal_(0, 1)
         label = torch.FloatTensor(batch_size)
         real_label = 1
         fake_label = 0