LookupTable doc typos (wrong axes order)

1 files changed, 9 insertions, 9 deletions

diff --git a/README.md b/README.md
index 4a71501..5048271 100644
--- a/README.md
+++ b/README.md
@@ -1732,7 +1732,7 @@ at `1` and can go up to `nIndex`. For each index, it outputs a corresponding `Te
 specified by `sizes` (a `LongStorage`) or `size1 x size2 x...`.
 
 Given a 1D input, the output tensors are concatenated, 
-generating a `size1 x size2 x ... x sizeN x n` tensor, where `n`
+generating a `n x size1 x size2 x ... x sizeN` tensor, where `n`
 is the size of a 1D `input` tensor. 
 
 Again with a 1D input, when only `size1` is provided, the `forward(input)` is equivalent to 
@@ -1748,21 +1748,21 @@ where `M` is a 2D matrix `size1 x nIndex` containing the parameters of the looku
  -- a lookup table containing 10 tensors of size 3
  module = nn.LookupTable(10, 3) 
 
- input = torch.Tensor(4)
- input[1] = 1; input[2] = 2; input[3] = 1; input[4] = 10;
+ input = torch.Tensor{1,2,1,10}
  print(module:forward(input))
 ```
 
 Outputs something like:
 ```lua
--0.1784  2.2045 -0.1784 -0.2475
--1.0120  0.0537 -1.0120 -0.2148
--1.2840  0.8685 -1.2840 -0.2792
-[torch.Tensor of dimension 3x4]
+-1.4415 -0.1001 -0.1708
+-0.6945 -0.4350  0.7977
+-1.4415 -0.1001 -0.1708
+-0.0745  1.9275  1.0915
+[torch.DoubleTensor of dimension 4x3]
 ```
-Note that the first column vector is the same than the 3rd one!
+Note that the first row vector is the same as the 3rd one!
 
-Given a 2D input tensor of size `m x n`, the output is a `m x size1 x size2 x ... x sizeN x n` 
+Given a 2D input tensor of size `m x n`, the output is a `m x n x size1 x size2 x ... x sizeN` 
 tensor, where `m` is the number of samples in 
 the batch and `n` is the number of indices per sample.