fix(mge/random): add lower bound and higher bound for uniform sampling

GitOrigin-RevId: 2a2c56fd17ea53b805a4a13906a9f9dd8ab0e133

python_module/megengine/random/distribution.py

@@ -62,12 +62,16 @@ def gaussian(
 @wrap_io_tensor
 def uniform(
     shape: Iterable[int],
+    low: float = 0,
+    high: float = 1,
     comp_node: Optional[CompNode] = None,
     comp_graph: Optional[CompGraph] = None,
 ) -> Tensor:
     r"""Random variable with uniform distribution $U(0, 1)$
 
     :param shape: Output tensor shape
+    :param low: Lower range
+    :param high: Upper range
     :param comp_node: The comp node output on, default to None
     :param comp_graph: The graph in which output is, default to None
     :return: The output tensor
@@ -91,6 +95,6 @@ def uniform(
     """
     comp_node, comp_graph = _use_default_if_none(comp_node, comp_graph)
     seed = _random_seed_generator().__next__()
-    return mgb.opr.uniform_rng(
+    return low + (high - low) * mgb.opr.uniform_rng(
         shape, seed=seed, comp_node=comp_node, comp_graph=comp_graph
     )

python_module/test/unit/random/test_random.py

@@ -59,6 +59,50 @@ def test_random_dynamic_same_result():
     assert np.all(a.numpy() == b.numpy())
 
 
+def test_range_uniform_static_diff_result():
+    @jit.trace(symbolic=True)
+    def graph_a():
+        return R.uniform(5, low=-2, high=2)
+
+    @jit.trace(symbolic=True)
+    def graph_b():
+        return R.uniform(5, low=-2, high=2)
+
+    a = graph_a()
+    b = graph_b()
+    assert np.any(a.numpy() != b.numpy())
+
+
+def test_range_uniform_static_same_result():
+    @jit.trace(symbolic=True)
+    def graph_a():
+        R.manual_seed(731)
+        return R.uniform(5, low=-2, high=2)
+
+    @jit.trace(symbolic=True)
+    def graph_b():
+        R.manual_seed(731)
+        return R.uniform(5, low=-2, high=2)
+
+    a = graph_a()
+    b = graph_b()
+    assert np.all(a.numpy() == b.numpy())
+
+
+def test_range_uniform_dynamic_diff_result():
+    a = R.uniform(5, low=-2, high=2)
+    b = R.uniform(5, low=-2, high=2)
+    assert np.any(a.numpy() != b.numpy())
+
+
+def test_range_uniform_dynamic_same_result():
+    R.manual_seed(0)
+    a = R.uniform(5, low=-2, high=2)
+    R.manual_seed(0)
+    b = R.uniform(5, low=-2, high=2)
+    assert np.all(a.numpy() == b.numpy())
+
+
 def test_dropout_dynamic_diff_result():
     x = mge.ones(10)
     a = F.dropout(x, 0.5)