add compose (k2-fsa#543)

* add compose.

* update doc.

* fix a typo.

* fix compose.

b_fsa.aux_labels can be a ragged tensor.

* add missing files for ragged shape doc.

* fix style issues.

.flake8

@@ -12,3 +12,5 @@ exclude =
 ignore =
   # E127 continuation line over-indented for visual indent
   E127,
+  # F401, import but not used
+  F401,

CMakeLists.txt

@@ -13,7 +13,7 @@ cmake_minimum_required(VERSION 3.8 FATAL_ERROR)
 
 project(k2 CUDA CXX)
 
-set(K2_VERSION "0.1.1")
+set(K2_VERSION "0.1.2")
 
 # ----------------- Supported build types for K2 project -----------------
 set(ALLOWABLE_BUILD_TYPES Debug Release RelWithDebInfo MinSizeRel)

docs/source/installation.rst

@@ -161,15 +161,26 @@ To run tests in parallel::
 
   cd build
   make -j
-  ctest --parallel <JOBNUM>
+  ctest --output-on-failure --parallel <JOBNUM>
 
 If `valgrind` is installed, you can check heap corruptions and memory leaks by::
 
   cd build
   make -j
-  ctest -R <TESTNAME> -D ExperimentalMemCheck
+  ctest --output-on-failure -R <TESTNAME> -D ExperimentalMemCheck
 
 .. HINT::
 
   You can install `valgrind` with `sudo apt-get install valgrind`
   on Ubuntu.
+
+Reporting issues
+----------------
+
+If you encounter any errors while using k2 after installation, please
+create an issue `on GitHub <https://github.com/k2-fsa/k2/issues/new>`_
+and tell us your current environment by posting the output of the following
+two commands::
+
+  python3 -m k2.version
+  python3 -m torch.utils.collect_env

docs/source/python_api/fsa_algo.rst

@@ -22,6 +22,11 @@ connect
 
 .. autofunction:: connect
 
+compose
+-------
+
+.. autofunction:: compose
+
 determinize
 -----------
 
@@ -47,6 +52,11 @@ intersect_dense_pruned
 
 .. autofunction:: intersect_dense_pruned
 
+invert
+------
+
+.. autofunction:: invert
+
 linear_fsa
 ----------
 
@@ -57,6 +67,11 @@ remove_epsilon
 
 .. autofunction:: remove_epsilon
 
+remove_epsilons_iterative_tropical
+----------------------------------
+
+.. autofunction:: remove_epsilons_iterative_tropical
+
 shortest_path
 -------------
 

docs/source/python_api/index.rst

@@ -14,4 +14,5 @@ Python API Reference
    version
    ops
    ragged_ops
+   ragged_shape
    _k2

docs/source/python_api/ragged_ops.rst

@@ -8,6 +8,11 @@ index
 
 .. autofunction:: index
 
+remove_axis
+-----------
+
+.. autofunction:: remove_axis
+
 remove_values_leq
 ------------------
 

docs/source/python_api/ragged_shape.rst

@@ -0,0 +1,15 @@
+ragged_shape
+============
+
+.. currentmodule:: k2.ragged
+
+create_ragged_shape2
+--------------------
+
+.. autofunction:: create_ragged_shape2
+
+
+compose_ragged_shapes
+---------------------
+
+.. autofunction:: compose_ragged_shapes

k2/python/k2/__init__.py

@@ -10,15 +10,16 @@
 from . import utils
 
 from .autograd import get_tot_scores
-from .autograd import intersect_dense_pruned
 from .autograd import intersect_dense
+from .autograd import intersect_dense_pruned
 from .autograd import union
 from .dense_fsa_vec import DenseFsaVec
 from .dense_fsa_vec import convert_dense_to_fsa_vec
 from .fsa import Fsa
 from .fsa_algo import add_epsilon_self_loops
 from .fsa_algo import arc_sort
 from .fsa_algo import closure
+from .fsa_algo import compose
 from .fsa_algo import connect
 from .fsa_algo import determinize
 from .fsa_algo import intersect
@@ -48,13 +49,14 @@
 __all__ = [
     'DenseFsaVec',
     'Fsa',
-    'SymbolTable',
     'RaggedInt',
     'RaggedShape',
+    'SymbolTable',
     'add_epsilon_self_loops',
     'arc_sort',
     'autograd_utils',
     'closure',
+    'compose',
     'connect',
     'convert_dense_to_fsa_vec',
     'create_fsa_vec',
@@ -83,5 +85,4 @@
     'to_tensor',
     'top_sort',
     'union',
-    'use_cuda',
 ]

k2/python/k2/fsa.py

@@ -19,7 +19,6 @@
 from _k2 import RaggedArc
 
 
-
 class Fsa(object):
     '''This class represents a single fsa or a vector of fsas.
 
@@ -436,7 +435,7 @@ def get_incoming_arcs(self) -> _k2.RaggedInt:
         name, cache = 'incoming_arcs', self._cache
         if name not in cache:
             cache[name] = _k2.get_incoming_arcs(self.arcs,
-                                                 self.get_dest_states())
+                                                self.get_dest_states())
         return cache[name]
 
     def get_entering_arc_batches(self) -> _k2.RaggedInt:
@@ -770,7 +769,8 @@ def __getitem__(self, i: int) -> 'Fsa':
 
         # The following is a magic invocation to make sure
         # the backprop on the scores happens.
-        k2.autograd_utils.phantom_set_scores_to(out_fsa, self.scores[start:end])
+        k2.autograd_utils.phantom_set_scores_to(out_fsa,
+                                                self.scores[start:end])
 
         return out_fsa