From ddacae58e1d82e8ff38d0f1a7c4716d20ce0956e Mon Sep 17 00:00:00 2001 From: Matthew Brookhart Date: Mon, 6 Jul 2020 09:25:01 -0700 Subject: [PATCH] respond to review comments. Thanks @siju-samuel --- python/tvm/relay/op/dyn/_transform.py | 2 +- tests/python/relay/dyn/test_dynamic_op_level3.py | 3 --- topi/include/topi/transform.h | 4 +--- 3 files changed, 2 insertions(+), 7 deletions(-) diff --git a/python/tvm/relay/op/dyn/_transform.py b/python/tvm/relay/op/dyn/_transform.py index 69004a2ac270..f7ffe895b48b 100644 --- a/python/tvm/relay/op/dyn/_transform.py +++ b/python/tvm/relay/op/dyn/_transform.py @@ -102,5 +102,5 @@ def tile_shape_func(attrs, inputs, _): """ ndim = len(inputs[0].shape) rdim = inputs[1].shape[0].value - assert ndim == rdim, "tile data and res ranks don't match" + assert ndim == rdim, "tile data and reps ranks don't match" return [_tile_shape_func(inputs[0], inputs[1], convert(ndim))] diff --git a/tests/python/relay/dyn/test_dynamic_op_level3.py b/tests/python/relay/dyn/test_dynamic_op_level3.py index 2b7b0aa928e7..176641583026 100644 --- a/tests/python/relay/dyn/test_dynamic_op_level3.py +++ b/tests/python/relay/dyn/test_dynamic_op_level3.py @@ -79,9 +79,6 @@ def verify_tile(dshape, reps): func = relay.Function([x, r], z) x_data = np.random.uniform(low=-1, high=1, size=dshape).astype("float32") ref_res = np.tile(x_data, reps=reps) - print (ref_res.shape) - print(x_data.shape) - print(np.array(reps).shape) verify_func(func, [x_data, np.array(reps).astype("float32")], ref_res) verify_tile((2, 3, 4), (3, 2, 1)) verify_tile((2, 3, 4), (1, 2, 1)) diff --git a/topi/include/topi/transform.h b/topi/include/topi/transform.h index 2fff9546312e..ed824e7a150b 100644 --- a/topi/include/topi/transform.h +++ b/topi/include/topi/transform.h @@ -1020,7 +1020,7 @@ inline Tensor tile(const Tensor& x, Array reps, std::string name = "T_t * \brief Creates an operation to tile elements of an array * * \param x The input tensor - * \param reps The number of times for repeating the tensor + * \param new_shape The shape of the output after tiling * \param name The name of the operation * \param tag The tag to mark the operation * @@ -1029,8 +1029,6 @@ inline Tensor tile(const Tensor& x, Array reps, std::string name = "T_t inline Tensor dyn_tile(const Tensor& x, Array new_shape, std::string name = "T_tile", std::string tag = kBroadcast) { size_t ndim = x->shape.size(); - std::cout << ndim << std::endl; - std::cout << new_shape << std::endl; if (is_empty_shape(new_shape)) { return compute( new_shape, [&](const Array& indices) { return tvm::cast(x->dtype, 0); }, name, tag);