Skip to content

Fixed .full() on master pytorch #7

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
Aelphy wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Fixed .full() on master pytorch #7

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion t3nsor/decompositions.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@ def to_tt_tensor(tens, max_tt_rank=10, epsilon=None):
for core_idx in range(d - 1):
curr_mode = shape[core_idx]
rows = ranks[core_idx] * curr_mode
tens = tens.view(rows, -1)
tens = tens.reshape(rows, -1)
columns = tens.shape[1]
u, s, v = svd_fix(tens)
if max_tt_rank[core_idx + 1] == 1:
Expand Down
18 changes: 9 additions & 9 deletions t3nsor/tensor_train.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ def __init__(self, tt_cores, shape=None, tt_ranks=None, convert_to_tensors=True)
self._parameter = None
self._dof = np.sum([np.prod(list(tt_core.shape)) for tt_core in self._tt_cores])
self._total = np.prod(self._shape)


@property
def tt_cores(self):
Expand Down Expand Up @@ -73,15 +73,15 @@ def parameter(self):
return self._parameter
else:
raise ValueError('Not a parameter, run .to_parameter() first')

@property
def dof(self):
return self._dof

@property
def total(self):
return self._total


def to(self, device):
new_cores = []
Expand Down Expand Up @@ -109,7 +109,7 @@ def to_parameter(self):
new_cores.append(core)

tt_p = TensorTrain(new_cores, convert_to_tensors=False)
tt_p._parameter = nn.ParameterList(tt_p.tt_cores)
tt_p._parameter = nn.ParameterList(tt_p.tt_cores)
tt_p._is_parameter = True
return tt_p

Expand All @@ -122,7 +122,7 @@ def full(self):

for i in range(1, num_dims):
res = res.view(-1, ranks[i])
curr_core = self.tt_cores[i].view(ranks[i], -1)
curr_core = self.tt_cores[i].reshape(ranks[i], -1)
res = torch.matmul(res, curr_core)

if self.is_tt_matrix:
Expand All @@ -138,7 +138,7 @@ def full(self):
for i in range(1, 2 * num_dims, 2):
transpose.append(i)
res = res.permute(*transpose)

if self.is_tt_matrix:
res = res.contiguous().view(*shape)
else:
Expand Down Expand Up @@ -268,8 +268,8 @@ def full(self):
for i in range(1, 2 * num_dims, 2):
transpose.append(i + 1)
res = res.permute(transpose)
if self.is_tt_matrix:

if self.is_tt_matrix:
res = res.contiguous().view(*shape)
else:
res = res.view(*shape)
Expand Down