ci(mge): remove blank line for windows doctest

GitOrigin-RevId: 09cf6518e8cf96113f455a6222ba17f271143bb4

imperative/python/megengine/functional/tensor.py

@@ -208,25 +208,16 @@ def broadcast_to(inp: Tensor, shape: Union[int, Iterable[int]]) -> Tensor:
         from megengine import tensor
         import megengine.functional as F
 
-        data = tensor(np.arange(0, 6, dtype=np.float32).reshape(2, 3))
-        out = F.broadcast_to(data, (4, 2, 3))
+        data = tensor(np.arange(0, 3, dtype=np.float32).reshape(3))
+        out = F.broadcast_to(data, (2, 3))
         print(out.numpy())
 
     Outputs:
 
     .. testoutput::
 
-        [[[0. 1. 2.]
-          [3. 4. 5.]]
-
-         [[0. 1. 2.]
-          [3. 4. 5.]]
-
-         [[0. 1. 2.]
-          [3. 4. 5.]]
-
-         [[0. 1. 2.]
-          [3. 4. 5.]]]
+        [[0. 1. 2.]
+         [0. 1. 2.]]
 
     """
     return _broadcast(inp, shape)
@@ -298,8 +289,8 @@ def stack(inps, axis=0, device=None):
         from megengine import tensor
         import megengine.functional as F
 
-        x1 = tensor(np.arange(0, 6, dtype=np.float32).reshape((2, 3)))
-        x2 = tensor(np.arange(6, 12, dtype=np.float32).reshape((2, 3)))
+        x1 = tensor(np.arange(0, 3, dtype=np.float32).reshape((3)))
+        x2 = tensor(np.arange(6, 9, dtype=np.float32).reshape((3)))
         out = F.stack([x1, x2], axis=0)
         print(out.numpy())
 
@@ -307,11 +298,8 @@ def stack(inps, axis=0, device=None):
 
     .. testoutput::
 
-        [[[ 0.  1.  2.]
-          [ 3.  4.  5.]]
-
-         [[ 6.  7.  8.]
-          [ 9. 10. 11.]]]
+        [[0. 1. 2.]
+         [6. 7. 8.]]
 
     """
     if len(inps) > 0 and not isinstance(inps[0].shape, inps[0].__class__):
@@ -751,21 +739,16 @@ def reshape(inp: Tensor, target_shape: Iterable[int]) -> Tensor:
         from megengine import tensor
         import megengine.functional as F
         x = tensor(np.arange(12, dtype=np.int32))
-        out = F.reshape(x, (3, 2, 2))
+        out = F.reshape(x, (3, 4))
         print(out.numpy())
 
     Outputs:
 
     .. testoutput::
 
-        [[[ 0  1]
-          [ 2  3]]
-
-         [[ 4  5]
-          [ 6  7]]
-
-         [[ 8  9]
-          [10 11]]]
+        [[ 0  1  2  3]
+         [ 4  5  6  7]
+         [ 8  9 10 11]]
 
     """
     return inp.reshape(target_shape)

imperative/python/megengine/module/embedding.py

@@ -38,10 +38,10 @@ class Embedding(Module):
         import numpy as np
         import megengine as mge
         import megengine.module as M
-        weight = mge.tensor(np.array([(1.2,2.3,3.4,4.5,5.6),(0.1,1.1,2.1,3.1,4.1)], dtype=np.float32))
-        data = mge.tensor(np.array([(0,1,1),(1,0,1),(0,0,1)], dtype=np.int32))
+        weight = mge.tensor(np.array([(1.2,2.3,3.4,4.5,5.6)], dtype=np.float32))
+        data = mge.tensor(np.array([(0,0)], dtype=np.int32))
 
-        embedding = M.Embedding(2, 5, initial_weight=weight)
+        embedding = M.Embedding(1, 5, initial_weight=weight)
         output = embedding(data)
         with np.printoptions(precision=6):
             print(output.numpy())
@@ -51,16 +51,7 @@ class Embedding(Module):
     .. testoutput::
 
         [[[1.2 2.3 3.4 4.5 5.6]
-          [0.1 1.1 2.1 3.1 4.1]
-          [0.1 1.1 2.1 3.1 4.1]]
-
-         [[0.1 1.1 2.1 3.1 4.1]
-          [1.2 2.3 3.4 4.5 5.6]
-          [0.1 1.1 2.1 3.1 4.1]]
-
-         [[1.2 2.3 3.4 4.5 5.6]
-          [1.2 2.3 3.4 4.5 5.6]
-          [0.1 1.1 2.1 3.1 4.1]]]
+          [1.2 2.3 3.4 4.5 5.6]]]
 
     """
 
@@ -134,8 +125,8 @@ class Embedding(Module):
             import numpy as np
             import megengine as mge
             import megengine.module as M
-            weight = mge.tensor(np.array([(1.2,2.3,3.4,4.5,5.6),(0.1,1.1,2.1,3.1,4.1)], dtype=np.float32))
-            data = mge.tensor(np.array([(0,1,1),(1,0,1),(0,0,1)], dtype=np.int32))
+            weight = mge.tensor(np.array([(1.2,2.3,3.4,4.5,5.6)], dtype=np.float32))
+            data = mge.tensor(np.array([(0,0)], dtype=np.int32))
 
             embedding = M.Embedding.from_pretrained(weight, freeze=False)
             output = embedding(data)
@@ -146,17 +137,7 @@ class Embedding(Module):
         .. testoutput::
 
             [[[1.2 2.3 3.4 4.5 5.6]
-              [0.1 1.1 2.1 3.1 4.1]
-              [0.1 1.1 2.1 3.1 4.1]]
-
-             [[0.1 1.1 2.1 3.1 4.1]
-              [1.2 2.3 3.4 4.5 5.6]
-              [0.1 1.1 2.1 3.1 4.1]]
-
-             [[1.2 2.3 3.4 4.5 5.6]
-              [1.2 2.3 3.4 4.5 5.6]
-              [0.1 1.1 2.1 3.1 4.1]]]
-
+              [1.2 2.3 3.4 4.5 5.6]]]
 
         """
         embeddings_shape = embeddings.shape