提交 d44dbc4a 编写于 作者: F fengjiayi

fix errors

上级 3e7ce583
......@@ -129,7 +129,7 @@ struct RandomCropFunctor {
for (int i = num_batchsize_dims_; i < rank_; ++i) {
typename Random<DeviceContext>::template UniformIntDist<size_t> dist(
0, x_dims_[i] - out_dims_[i]);
offsets[i] = dist(engine);
offsets[i - num_batchsize_dims_] = dist(engine);
}
const T* x = x_ + ins_idx * prod_x_ins_dims_;
......
......@@ -336,6 +336,8 @@ class OpTest(unittest.TestCase):
actual_t = np.array(actual)
expect = self.outputs[out_name]
expect_t = expect[0] if isinstance(expect, tuple) else expect
import pdb
pdb.set_trace()
self.assertTrue(
np.allclose(
actual_t, expect_t, atol=atol),
......
......@@ -20,14 +20,26 @@ from op_test import OpTest
class TestRandomCropOp(OpTest):
def setUp(self):
to_crop = np.random.random((1, 10, 15)).astype("float32")
to_crop = np.array([[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]] *
5).astype("float32")
self.possible_res = [
np.array([[1, 2, 3], [5, 6, 7]]), np.array([[2, 3, 4], [6, 7, 8]]),
np.array([[5, 6, 7], [9, 10, 11]]),
np.array([[6, 7, 8], [10, 11, 12]])
]
self.op_type = "random_crop"
self.inputs = {'X': to_crop, 'Seed': np.array([10])}
self.outputs = {'Out': np.array([1, 2, 3]), 'SeedOut': np.array([2])}
self.attrs = {'shape': [5, 5]}
self.outputs = {'Out': np.array([]), 'SeedOut': np.array([])}
self.attrs = {'shape': [2, 3]}
def test_check_output(self):
self.check_output()
self.check_output_customized(self.verify_output)
def verify_output(self, outs):
out = np.array(outs[1])
for ins in out[:]:
is_equal = [(ins == res).all() for res in self.possible_res]
self.assertIn(True, is_equal)
if __name__ == "__main__":
......
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