fix `TypeError: arrays to stack must be passed as a "sequence" type s…

…uch as list or tuple.`
apache · Oct 30, 2024 · f2730a4 · f2730a4
1 parent f6ccb7b
commit f2730a4
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Showing 3 changed files with 8 additions and 8 deletions.
diff --git a/python/tvm/contrib/sparse.py b/python/tvm/contrib/sparse.py
@@ -95,7 +95,7 @@ def numpy(self):
         """Construct a full matrix and convert it to numpy array."""
         full = _np.zeros(self.shape, self.dtype)
         ridx = _np.diff(self.indptr.numpy())
-        ridx = _np.hstack((_np.ones((v,), itype) * i for i, v in enumerate(ridx)))
+        ridx = _np.hstack([_np.ones((v,), itype) * i for i, v in enumerate(ridx)])
         full[ridx, self.indices.numpy().astype(itype)] = self.data.numpy()
         return full
 

diff --git a/tests/python/contrib/test_cublas.py b/tests/python/contrib/test_cublas.py
@@ -82,22 +82,22 @@ def verify(target="cuda"):
         b_old = np.random.uniform(0, 128, size=(l, m))
 
         # Transform a to become CUBLASLT_ORDER_COL4_4R2_8C layout
-        a_new = np.hstack((a_old.astype(A.dtype), np.zeros([n, L - l])))
-        a_new = np.vstack((a_new.astype(A.dtype), np.zeros([N - n, L])))
+        a_new = np.hstack([a_old.astype(A.dtype), np.zeros([n, L - l])])
+        a_new = np.vstack([a_new.astype(A.dtype), np.zeros([N - n, L])])
         a_even = np.vsplit(a_new[::2], N / 8)
         a_odd = np.vsplit(a_new[1::2], N / 8)
         a_new = [None] * (len(a_even) + len(a_odd))
         a_new[::2] = a_even
         a_new[1::2] = a_odd
         a_new = np.vstack(a_new)
-        a_new = np.vstack(
-            np.vstack(np.vstack(np.hsplit(i, 8)).reshape([4, 32]) for i in np.vsplit(j, N / 4))
+        a_new = np.vstack([
+            np.vstack([np.vstack(np.hsplit(i, 8)).reshape([4, 32]) for i in np.vsplit(j, N / 4)])
             for j in np.hsplit(a_new, L / 32)
-        )
+        ])
         a_new = a_new.reshape([N, L])
         # Transform b to become CUBLASLT_ORDER_COL32 layout
         b_new = np.vstack(
-            np.hsplit(np.hstack((b_old.T.astype(B.dtype), np.zeros([m, L - l]))), L / 32)
+            np.hsplit(np.hstack([b_old.T.astype(B.dtype), np.zeros([m, L - l])]), L / 32)
         )
         b_new = b_new.reshape([m, L])
 

diff --git a/tests/python/frontend/coreml/test_forward.py b/tests/python/frontend/coreml/test_forward.py
@@ -306,7 +306,7 @@ def _verify_average(input_dim1, input_dim2, axis=0):
     a_np1 = np.random.uniform(size=input_dim1).astype(dtype)
     a_np2 = np.random.uniform(size=input_dim2).astype(dtype)
 
-    b_np = np.mean((a_np1, a_np2), axis=axis)
+    b_np = np.mean((a_np1, a_np2), axis=axis, dtype=float)
 
     inputs = [("input1", datatypes.Array(*input_dim1)), ("input2", datatypes.Array(*input_dim2))]
     output = [("output", datatypes.Array(*b_np.shape))]