lixiaoquan commented on a change in pull request #5429:
URL: https://github.com/apache/incubator-tvm/pull/5429#discussion_r420541474
##########
File path: tests/python/relay/test_any.py
##########
@@ -138,23 +138,35 @@ def test_any_concat():
result = ex.evaluate()(x_np, y_np)
tvm.testing.assert_allclose(result.asnumpy(), ref)
-def verify_any_reshape(x_shape, newshape, x_np_shape, out_shape):
+def verify_any_reshape(x_shape, newshape, x_np_shape, out_shape,
variable_newshape=False):
x = relay.var('x', shape=x_shape, dtype="float32")
+ data = np.random.uniform(size=x_np_shape).astype('float32')
+ params = [x]
+ args = [data]
+
+ if variable_newshape:
+ newshape_var = relay.var('newshape', shape=(len(newshape),),
dtype='int64')
+ params.append(newshape_var)
+ args.append(np.array(newshape, dtype='int64'))
+ newshape = newshape_var
+
y = relay.reshape(x, newshape=newshape)
mod = tvm.IRModule()
- mod["main"] = relay.Function([x], y)
- data = np.random.uniform(size=x_np_shape).astype('float32')
+ mod["main"] = relay.Function(params, y)
+
for kind in ["debug", "vm"]:
ex = relay.create_executor(kind, mod=mod, ctx=tvm.cpu(), target="llvm")
- result = ex.evaluate()(data).asnumpy()
+ result = ex.evaluate()(*args).asnumpy()
assert result.shape == out_shape
tvm.testing.assert_allclose(result.flatten(), data.flatten())
def test_any_reshape():
- verify_any_reshape(any_dims(3), (1, -1), (2, 3, 4), (1, 24))
- verify_any_reshape(any_dims(3), (0, -1), (2, 3, 4), (2, 12))
+ for variable_newshape in [False, True]:
+ # Variable newshape only supports that output rank is the same as
newshape
Review comment:
Do you mean add some dynamic shape cases to test_op_level3? Cases in
that file use 'graph' exectuor now and test like test_arange() only supports
constant inputs too.
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