diff --git a/eagerpy/framework.py b/eagerpy/framework.py
index 40a24e8..49a241d 100644
--- a/eagerpy/framework.py
+++ b/eagerpy/framework.py
@@ -1,4 +1,4 @@
-from typing import overload, Sequence, Callable, Tuple, Any, Optional, cast
+from typing import overload, Sequence, Callable, Tuple, Any, Optional, cast, Union
 from typing_extensions import Literal
 
 from .types import Axes, AxisAxes, Shape, ShapeOrScalar
@@ -348,7 +348,7 @@ def value_aux_and_grad(
     return t.value_aux_and_grad(f, *args, **kwargs)
 
 
-def reshape(t: TensorType, shape: Shape) -> TensorType:
+def reshape(t: TensorType, shape: Union[Shape, int]) -> TensorType:
     return t.reshape(shape)
 
 
diff --git a/eagerpy/tensor/jax.py b/eagerpy/tensor/jax.py
index 14c9a73..0828114 100644
--- a/eagerpy/tensor/jax.py
+++ b/eagerpy/tensor/jax.py
@@ -108,7 +108,9 @@ def item(self) -> Union[int, float, bool]:
     def shape(self) -> Shape:
         return cast(Tuple, self.raw.shape)
 
-    def reshape(self: TensorType, shape: Shape) -> TensorType:
+    def reshape(self: TensorType, shape: Union[Shape, int]) -> TensorType:
+        if isinstance(shape, int):
+            shape = (shape,)
         return type(self)(self.raw.reshape(shape))
 
     def astype(self: TensorType, dtype: Any) -> TensorType:
diff --git a/eagerpy/tensor/numpy.py b/eagerpy/tensor/numpy.py
index fadbf52..0e03c83 100644
--- a/eagerpy/tensor/numpy.py
+++ b/eagerpy/tensor/numpy.py
@@ -56,7 +56,9 @@ def item(self) -> Union[int, float, bool]:
     def shape(self: TensorType) -> Shape:
         return cast(Tuple, self.raw.shape)
 
-    def reshape(self: TensorType, shape: Shape) -> TensorType:
+    def reshape(self: TensorType, shape: Union[Shape, int]) -> TensorType:
+        if isinstance(shape, int):
+            shape = (shape,)
         return type(self)(self.raw.reshape(shape))
 
     def astype(self: TensorType, dtype: Any) -> TensorType:
diff --git a/eagerpy/tensor/pytorch.py b/eagerpy/tensor/pytorch.py
index 3a942fc..62ed64d 100644
--- a/eagerpy/tensor/pytorch.py
+++ b/eagerpy/tensor/pytorch.py
@@ -71,7 +71,9 @@ def item(self) -> Union[int, float, bool]:
     def shape(self) -> Shape:
         return self.raw.shape
 
-    def reshape(self: TensorType, shape: Shape) -> TensorType:
+    def reshape(self: TensorType, shape: Union[Shape, int]) -> TensorType:
+        if isinstance(shape, int):
+            shape = (shape,)
         return type(self)(self.raw.reshape(shape))
 
     def astype(self: TensorType, dtype: Any) -> TensorType:
diff --git a/eagerpy/tensor/tensor.py b/eagerpy/tensor/tensor.py
index 108230f..0c9e846 100644
--- a/eagerpy/tensor/tensor.py
+++ b/eagerpy/tensor/tensor.py
@@ -235,7 +235,7 @@ def shape(self: TensorType) -> Shape:
         ...
 
     @abstractmethod
-    def reshape(self: TensorType, shape: Shape) -> TensorType:
+    def reshape(self: TensorType, shape: Union[Shape, int]) -> TensorType:
         ...
 
     @abstractmethod
diff --git a/eagerpy/tensor/tensorflow.py b/eagerpy/tensor/tensorflow.py
index ccc68e9..8b9ec9b 100644
--- a/eagerpy/tensor/tensorflow.py
+++ b/eagerpy/tensor/tensorflow.py
@@ -103,7 +103,9 @@ def item(self: TensorType) -> Union[int, float, bool]:
     def shape(self: TensorType) -> Shape:
         return tuple(self.raw.shape.as_list())
 
-    def reshape(self: TensorType, shape: Shape) -> TensorType:
+    def reshape(self: TensorType, shape: Union[Shape, int]) -> TensorType:
+        if isinstance(shape, int):
+            shape = (shape,)
         return type(self)(tf.reshape(self.raw, shape))
 
     def astype(self: TensorType, dtype: Any) -> TensorType:
diff --git a/tests/test_main.py b/tests/test_main.py
index c81bfe7..ae0a4bd 100644
--- a/tests/test_main.py
+++ b/tests/test_main.py
@@ -655,6 +655,19 @@ def test_reshape(t: Tensor) -> Tensor:
     return ep.reshape(t, shape)
 
 
+@compare_all
+def test_reshape_minus_1(t: Tensor) -> Tensor:
+    return ep.reshape(t, -1)
+
+
+@compare_all
+def test_reshape_int(t: Tensor) -> Tensor:
+    n = 1
+    for k in t.shape:
+        n *= k
+    return ep.reshape(t, n)
+
+
 @compare_all
 def test_clip(t: Tensor) -> Tensor:
     return ep.clip(t, 2, 3.5)