From debf72f80fe481e1269eb843c9575caf42fff9cc Mon Sep 17 00:00:00 2001 From: tomoyazhang Date: Thu, 13 Jan 2022 13:53:07 +0800 Subject: [PATCH] remove print --- python/tvm/relay/frontend/onnx.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/python/tvm/relay/frontend/onnx.py b/python/tvm/relay/frontend/onnx.py index 22990d7d36cb8..13be822b98ee5 100644 --- a/python/tvm/relay/frontend/onnx.py +++ b/python/tvm/relay/frontend/onnx.py @@ -238,7 +238,6 @@ def flatten_to_nd(x, x_shape, nd=3): out = _op.reshape(x, fold_constant(newshape)) return out - print("a_rank={} b_rank={}".format(a_rank, b_rank)) # Determine the output batch dimension. if a_rank > b_rank: out_batch = _op.strided_slice(a_shape, [0], [a_rank - 2]) @@ -284,8 +283,6 @@ def flatten_to_nd(x, x_shape, nd=3): ], 0, ) - print(fold_constant(a_broadcasted_shape).data.numpy()) - print(fold_constant(b_broadcasted_shape).data.numpy()) a = _op.transform.broadcast_to(inputs[0], fold_constant(a_broadcasted_shape)) b = _op.transform.broadcast_to(inputs[1], fold_constant(b_broadcasted_shape)) # Convert a and b into 3 dimensional tensors.