From 03d0792f913a52cbd1250cfa704090ae26930ab1 Mon Sep 17 00:00:00 2001
From: Mikhail Usvyatsov <m.usvyatsov@gmail.com>
Date: Mon, 26 Aug 2019 20:52:04 +0200
Subject: [PATCH] fixed full on master pytorch

---
 t3nsor/decompositions.py |  2 +-
 t3nsor/tensor_train.py   | 18 +++++++++---------
 2 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/t3nsor/decompositions.py b/t3nsor/decompositions.py
index 4bcf4e8..2da644a 100755
--- a/t3nsor/decompositions.py
+++ b/t3nsor/decompositions.py
@@ -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:
diff --git a/t3nsor/tensor_train.py b/t3nsor/tensor_train.py
index 4327d03..cbc634c 100755
--- a/t3nsor/tensor_train.py
+++ b/t3nsor/tensor_train.py
@@ -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):
@@ -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 = []
@@ -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
 
@@ -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:
@@ -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:
@@ -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)