wishful thinking. but what if...?

monotonic_align/__init__.py

@@ -1,19 +0,0 @@
-import numpy as np
-import torch
-from .monotonic_align.core import maximum_path_c
-
-
-def maximum_path(neg_cent, mask):
-  """ Cython optimized version.
-  neg_cent: [b, t_t, t_s]
-  mask: [b, t_t, t_s]
-  """
-  device = neg_cent.device
-  dtype = neg_cent.dtype
-  neg_cent = neg_cent.data.cpu().numpy().astype(np.float32)
-  path = np.zeros(neg_cent.shape, dtype=np.int32)
-
-  t_t_max = mask.sum(1)[:, 0].data.cpu().numpy().astype(np.int32)
-  t_s_max = mask.sum(2)[:, 0].data.cpu().numpy().astype(np.int32)
-  maximum_path_c(path, neg_cent, t_t_max, t_s_max)
-  return torch.from_numpy(path).to(device=device, dtype=dtype)

monotonic_align/core.pyx

@@ -1,42 +0,0 @@
-cimport cython
-from cython.parallel import prange
-
-
-@cython.boundscheck(False)
-@cython.wraparound(False)
-cdef void maximum_path_each(int[:,::1] path, float[:,::1] value, int t_y, int t_x, float max_neg_val=-1e9) nogil:
-  cdef int x
-  cdef int y
-  cdef float v_prev
-  cdef float v_cur
-  cdef float tmp
-  cdef int index = t_x - 1
-
-  for y in range(t_y):
-    for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)):
-      if x == y:
-        v_cur = max_neg_val
-      else:
-        v_cur = value[y-1, x]
-      if x == 0:
-        if y == 0:
-          v_prev = 0.
-        else:
-          v_prev = max_neg_val
-      else:
-        v_prev = value[y-1, x-1]
-      value[y, x] += max(v_prev, v_cur)
-
-  for y in range(t_y - 1, -1, -1):
-    path[y, index] = 1
-    if index != 0 and (index == y or value[y-1, index] < value[y-1, index-1]):
-      index = index - 1
-
-
-@cython.boundscheck(False)
-@cython.wraparound(False)
-cpdef void maximum_path_c(int[:,:,::1] paths, float[:,:,::1] values, int[::1] t_ys, int[::1] t_xs) nogil:
-  cdef int b = paths.shape[0]
-  cdef int i
-  for i in prange(b, nogil=True):
-    maximum_path_each(paths[i], values[i], t_ys[i], t_xs[i])

monotonic_align/monotonic_align/core.cpython-37m-x86_64-linux-gnu.so

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9b7860864450a414629fce8397c335fe0825bd0b1a98089233ef826c6758d649
-size 729352

monotonic_align/setup.py

@@ -1,9 +0,0 @@
-from distutils.core import setup
-from Cython.Build import cythonize
-import numpy
-
-setup(
-  name = 'monotonic_align',
-  ext_modules = cythonize("core.pyx"),
-  include_dirs=[numpy.get_include()]
-)

requirements.txt

@@ -5,4 +5,5 @@ numpy==1.21.6
 scipy==1.5.2
 tensorboard==2.3.0
 torch
-torchaudio
+torchaudio
+git+https://github.com/resemble-ai/monotonic_align.git