Update Python syntax

Author: master

examples/shared/utils.py

@@ -16,7 +16,7 @@ def download_data(data_dir, url, unpack=True, block_size=10 * 1024):
         print("{} already exists. Skipping download".format(filename))
         return
 
-    print("Downloading {0} to {1}".format(url, filename))
+    print("Downloading {} to {}".format(url, filename))
     response = requests.get(url, stream=True)
     total = int(response.headers.get("content-length", 0))
     progress_bar = tqdm.tqdm(total=total, unit="iB", unit_scale=True)
@@ -33,7 +33,7 @@ def download_data(data_dir, url, unpack=True, block_size=10 * 1024):
         with open(filename, "rb") as f:
             with zipfile.ZipFile(f) as zip_ref:
                 zip_ref.extractall(data_dir)
-        print("Unzipped {0} to {1}".format(filename, data_dir))
+        print("Unzipped {} to {}".format(filename, data_dir))
 
 
 def load_matlab_data(key, data_dir, *folders):

setup.py

@@ -5,7 +5,7 @@
     name="tensorflow-riemopt",
     version="0.1.2",
     description="a library for optimization on Riemannian manifolds",
-    long_description=open("README.md", "r").read(),
+    long_description=open("README.md").read(),
     long_description_content_type="text/markdown",
     author="Oleg Smirnov",
     author_email="[email protected]",

tensorflow_riemopt/manifolds/hyperboloid.py

@@ -24,7 +24,7 @@ def __init__(self, k=1.0):
         super().__init__()
 
     def __repr__(self):
-        return "{0} (k={1}, ndims={2}) manifold".format(
+        return "{} (k={}, ndims={}) manifold".format(
             self.name, self.k, self.ndims
         )
 

tensorflow_riemopt/manifolds/manifold.py

@@ -8,7 +8,7 @@ class Manifold(metaclass=abc.ABCMeta):
 
     def __repr__(self):
         """Returns a string representation of the particular manifold."""
-        return "{0} (ndims={1}) manifold".format(self.name, self.ndims)
+        return "{} (ndims={}) manifold".format(self.name, self.ndims)
 
     def check_shape(self, shape_or_tensor):
         """Check if given shape is compatible with the manifold."""

tensorflow_riemopt/manifolds/poincare.py

@@ -31,7 +31,7 @@ def __init__(self, k=1.0):
         super().__init__()
 
     def __repr__(self):
-        return "{0} (k={1}, ndims={2}) manifold".format(
+        return "{} (k={}, ndims={}) manifold".format(
             self.name, self.k, self.ndims
         )
 
@@ -45,10 +45,10 @@ def _check_vector_on_tangent(self, x, u, atol, rtol):
 
     def _mobius_add(self, x, y):
         """Compute the Möbius addition of :math:`x` and :math:`y` in
-        :math:`\mathcal{D}^{n}_{k}`
+        :math:`\\mathcal{D}^{n}_{k}`
 
-        :math:`x \oplus y = \frac{(1 + 2k\langle x, y\rangle + k||y||^2)x + (1
-            - k||x||^2)y}{1 + 2k\langle x,y\rangle + k^2||x||^2||y||^2}`
+        :math:`x \\oplus y = \frac{(1 + 2k\\langle x, y\rangle + k||y||^2)x + (1
+            - k||x||^2)y}{1 + 2k\\langle x,y\rangle + k^2||x||^2||y||^2}`
         """
         x_2 = tf.reduce_sum(tf.math.square(x), axis=-1, keepdims=True)
         y_2 = tf.reduce_sum(tf.math.square(y), axis=-1, keepdims=True)
@@ -59,11 +59,11 @@ def _mobius_add(self, x, y):
         )
 
     def _mobius_scal_mul(self, x, r):
-        """Compute the Möbius scalar multiplication of :math:`x \in
-        \mathcal{D}^{n}_{k} \ {0}` by :math:`r`
+        """Compute the Möbius scalar multiplication of :math:`x \\in
+        \\mathcal{D}^{n}_{k} \\ {0}` by :math:`r`
 
-        :math:`x \otimes r = (1/\sqrt{k})\tanh(r
-        \atanh(\sqrt{k}||x||))\frac{x}{||x||}`
+        :math:`x \\otimes r = (1/\\sqrt{k})\tanh(r
+        \atanh(\\sqrt{k}||x||))\frac{x}{||x||}`
 
         """
         sqrt_k = tf.math.sqrt(tf.cast(self.k, x.dtype))
@@ -73,7 +73,7 @@ def _mobius_scal_mul(self, x, r):
         return (1 / sqrt_k) * tf.math.tanh(r * tf.math.atanh(tan)) * x / norm_x
 
     def _gyration(self, u, v, w):
-        """Compute the gyration of :math:`u`, :math:`v`, :math:`w`:
+        r"""Compute the gyration of :math:`u`, :math:`v`, :math:`w`:
 
         :math:`\operatorname{gyr}[u, v]w =
         \ominus (u \oplus_\kappa v) \oplus (u \oplus_\kappa (v \oplus_\kappa w))`

tensorflow_riemopt/optimizers/constrained_rmsprop.py

@@ -66,7 +66,7 @@ def __init__(
             allow time inverse decay of learning rate. `lr` is included for backward
             compatibility, recommended to use `learning_rate` instead.
         """
-        super(ConstrainedRMSprop, self).__init__(name, **kwargs)
+        super().__init__(name, **kwargs)
         self._set_hyper("learning_rate", kwargs.get("lr", learning_rate))
         self._set_hyper("decay", self._initial_decay)
         self._set_hyper("rho", rho)
@@ -83,7 +83,7 @@ def _create_slots(self, var_list):
                 self.add_slot(var, "mg")
 
     def _prepare_local(self, var_device, var_dtype, apply_state):
-        super(ConstrainedRMSprop, self)._prepare_local(
+        super()._prepare_local(
             var_device, var_dtype, apply_state
         )
 
@@ -197,10 +197,10 @@ def set_weights(self, weights):
         params = self.weights
         if len(params) == len(weights) + 1:
             weights = [np.array(0)] + weights
-        super(ConstrainedRMSprop, self).set_weights(weights)
+        super().set_weights(weights)
 
     def get_config(self):
-        config = super(ConstrainedRMSprop, self).get_config()
+        config = super().get_config()
         config.update(
             {
                 "learning_rate": self._serialize_hyperparameter(

tensorflow_riemopt/optimizers/riemannian_adam.py

@@ -69,7 +69,7 @@ def __init__(
 
         """
 
-        super(RiemannianAdam, self).__init__(name, **kwargs)
+        super().__init__(name, **kwargs)
         self._set_hyper("learning_rate", kwargs.get("lr", learning_rate))
         self._set_hyper("decay", self._initial_decay)
         self._set_hyper("beta_1", beta_1)
@@ -88,7 +88,7 @@ def _create_slots(self, var_list):
                 self.add_slot(var, "vhat")
 
     def _prepare_local(self, var_device, var_dtype, apply_state):
-        super(RiemannianAdam, self)._prepare_local(
+        super()._prepare_local(
             var_device, var_dtype, apply_state
         )
 
@@ -118,7 +118,7 @@ def set_weights(self, weights):
         num_vars = int((len(params) - 1) / 2)
         if len(weights) == 3 * num_vars + 1:
             weights = weights[: len(params)]
-        super(RiemannianAdam, self).set_weights(weights)
+        super().set_weights(weights)
 
     @def_function.function(experimental_compile=True)
     def _resource_apply_dense(self, grad, var, apply_state=None):
@@ -215,7 +215,7 @@ def _stabilize(self, var):
             m.assign(manifold.proju(var, m))
 
     def get_config(self):
-        config = super(RiemannianAdam, self).get_config()
+        config = super().get_config()
         config.update(
             {
                 "learning_rate": self._serialize_hyperparameter(

tensorflow_riemopt/optimizers/riemannian_gradient_descent.py

@@ -57,7 +57,7 @@ def __init__(
 
         """
 
-        super(RiemannianSGD, self).__init__(name, **kwargs)
+        super().__init__(name, **kwargs)
         self._set_hyper("learning_rate", kwargs.get("lr", learning_rate))
         self._set_hyper("decay", self._initial_decay)
         self._momentum = False
@@ -81,7 +81,7 @@ def _create_slots(self, var_list):
                 self.add_slot(var, "momentum")
 
     def _prepare_local(self, var_device, var_dtype, apply_state):
-        super(RiemannianSGD, self)._prepare_local(
+        super()._prepare_local(
             var_device, var_dtype, apply_state
         )
         apply_state[(var_device, var_dtype)]["momentum"] = array_ops.identity(
@@ -168,7 +168,7 @@ def _stabilize(self, var):
                 momentum.assign(manifold.proju(var, momentum))
 
     def get_config(self):
-        config = super(RiemannianSGD, self).get_config()
+        config = super().get_config()
         config.update(
             {
                 "learning_rate": self._serialize_hyperparameter(