We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
diagflat


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `ivy/functional/frontends/numpy/creation_routines/building_matrices.py`
Content:
```
1 import ivy
2 from ivy.functional.frontends.numpy.func_wrapper import (
3     to_ivy_arrays_and_back,
4     handle_numpy_dtype,
5 )
6 
7 
8 @to_ivy_arrays_and_back
9 def tril(m, k=0):
10     return ivy.tril(m, k=k)
11 
12 
13 @to_ivy_arrays_and_back
14 def triu(m, k=0):
15     return ivy.triu(m, k=k)
16 
17 
18 @handle_numpy_dtype
19 @to_ivy_arrays_and_back
20 def tri(N, M=None, k=0, dtype="float64", *, like=None):
21     if M is None:
22         M = N
23     ones = ivy.ones((N, M), dtype=dtype)
24     return ivy.tril(ones, k=k)
25 
26 
27 @to_ivy_arrays_and_back
28 def diag(v, k=0):
29     return ivy.diag(v, k=k)
30 
31 
32 @to_ivy_arrays_and_back
33 def vander(x, N=None, increasing=False):
34     if ivy.is_float_dtype(x):
35         x = x.astype(ivy.float64)
36     elif ivy.is_bool_dtype or ivy.is_int_dtype(x):
37         x = x.astype(ivy.int64)
38     return ivy.vander(x, N=N, increasing=increasing)
39
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/ivy/functional/frontends/numpy/creation_routines/building_matrices.py b/ivy/functional/frontends/numpy/creation_routines/building_matrices.py
--- a/ivy/functional/frontends/numpy/creation_routines/building_matrices.py
+++ b/ivy/functional/frontends/numpy/creation_routines/building_matrices.py
@@ -36,3 +36,12 @@
     elif ivy.is_bool_dtype or ivy.is_int_dtype(x):
         x = x.astype(ivy.int64)
     return ivy.vander(x, N=N, increasing=increasing)
+
+
+# diagflat
+@to_ivy_arrays_and_back
+def diagflat(v, k=0):
+    ret = ivy.diagflat(v, offset=k)
+    while len(ivy.shape(ret)) < 2:
+        ret = ret.expand_dims(axis=0)
+    return ret

{"golden_diff": "diff --git a/ivy/functional/frontends/numpy/creation_routines/building_matrices.py b/ivy/functional/frontends/numpy/creation_routines/building_matrices.py\n--- a/ivy/functional/frontends/numpy/creation_routines/building_matrices.py\n+++ b/ivy/functional/frontends/numpy/creation_routines/building_matrices.py\n@@ -36,3 +36,12 @@\n     elif ivy.is_bool_dtype or ivy.is_int_dtype(x):\n         x = x.astype(ivy.int64)\n     return ivy.vander(x, N=N, increasing=increasing)\n+\n+\n+# diagflat\n+@to_ivy_arrays_and_back\n+def diagflat(v, k=0):\n+    ret = ivy.diagflat(v, offset=k)\n+    while len(ivy.shape(ret)) < 2:\n+        ret = ret.expand_dims(axis=0)\n+    return ret\n", "issue": "diagflat\n\n", "before_files": [{"content": "import ivy\nfrom ivy.functional.frontends.numpy.func_wrapper import (\n    to_ivy_arrays_and_back,\n    handle_numpy_dtype,\n)\n\n\n@to_ivy_arrays_and_back\ndef tril(m, k=0):\n    return ivy.tril(m, k=k)\n\n\n@to_ivy_arrays_and_back\ndef triu(m, k=0):\n    return ivy.triu(m, k=k)\n\n\n@handle_numpy_dtype\n@to_ivy_arrays_and_back\ndef tri(N, M=None, k=0, dtype=\"float64\", *, like=None):\n    if M is None:\n        M = N\n    ones = ivy.ones((N, M), dtype=dtype)\n    return ivy.tril(ones, k=k)\n\n\n@to_ivy_arrays_and_back\ndef diag(v, k=0):\n    return ivy.diag(v, k=k)\n\n\n@to_ivy_arrays_and_back\ndef vander(x, N=None, increasing=False):\n    if ivy.is_float_dtype(x):\n        x = x.astype(ivy.float64)\n    elif ivy.is_bool_dtype or ivy.is_int_dtype(x):\n        x = x.astype(ivy.int64)\n    return ivy.vander(x, N=N, increasing=increasing)\n", "path": "ivy/functional/frontends/numpy/creation_routines/building_matrices.py"}], "after_files": [{"content": "import ivy\nfrom ivy.functional.frontends.numpy.func_wrapper import (\n    to_ivy_arrays_and_back,\n    handle_numpy_dtype,\n)\n\n\n@to_ivy_arrays_and_back\ndef tril(m, k=0):\n    return ivy.tril(m, k=k)\n\n\n@to_ivy_arrays_and_back\ndef triu(m, k=0):\n    return ivy.triu(m, k=k)\n\n\n@handle_numpy_dtype\n@to_ivy_arrays_and_back\ndef tri(N, M=None, k=0, dtype=\"float64\", *, like=None):\n    if M is None:\n        M = N\n    ones = ivy.ones((N, M), dtype=dtype)\n    return ivy.tril(ones, k=k)\n\n\n@to_ivy_arrays_and_back\ndef diag(v, k=0):\n    return ivy.diag(v, k=k)\n\n\n@to_ivy_arrays_and_back\ndef vander(x, N=None, increasing=False):\n    if ivy.is_float_dtype(x):\n        x = x.astype(ivy.float64)\n    elif ivy.is_bool_dtype or ivy.is_int_dtype(x):\n        x = x.astype(ivy.int64)\n    return ivy.vander(x, N=N, increasing=increasing)\n\n\n# diagflat\n@to_ivy_arrays_and_back\ndef diagflat(v, k=0):\n    ret = ivy.diagflat(v, offset=k)\n    while len(ivy.shape(ret)) < 2:\n        ret = ret.expand_dims(axis=0)\n    return ret\n", "path": "ivy/functional/frontends/numpy/creation_routines/building_matrices.py"}]}