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Posted to commits@tvm.apache.org by zh...@apache.org on 2020/03/11 15:30:24 UTC
[incubator-tvm] branch master updated: [QNN] Support 4D padding.
(#5036)
This is an automated email from the ASF dual-hosted git repository.
zhaowu pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/master by this push:
new 0755e4a [QNN] Support 4D padding. (#5036)
0755e4a is described below
commit 0755e4a58897c64d6a7ffc86bab3df45554bac7e
Author: Animesh Jain <an...@umich.edu>
AuthorDate: Wed Mar 11 08:30:13 2020 -0700
[QNN] Support 4D padding. (#5036)
* [QNN] Support 4D padding.
* Empty commit.
Co-authored-by: Ubuntu <ub...@ip-172-31-38-96.us-west-2.compute.internal>
---
python/tvm/relay/qnn/op/qnn.py | 4 ++++
src/relay/qnn/op/convolution.cc | 17 ++++++++++-------
tests/python/relay/test_op_qnn_conv2d.py | 24 ++++++++++++++++++++++++
3 files changed, 38 insertions(+), 7 deletions(-)
diff --git a/python/tvm/relay/qnn/op/qnn.py b/python/tvm/relay/qnn/op/qnn.py
index a7529f6..c94a419 100644
--- a/python/tvm/relay/qnn/op/qnn.py
+++ b/python/tvm/relay/qnn/op/qnn.py
@@ -19,6 +19,7 @@
from __future__ import absolute_import as _abs
from tvm.relay.expr import Tuple
+from tvm.relay.op.nn.util import get_pad_tuple2d
from . import _make
def requantize(data,
@@ -280,6 +281,9 @@ def conv2d(data,
The computed result.
"""
+ # TODO enforce 4-way padding in topi/nn/conv2d after #4644 merged
+ # convert 2-way padding to 4-way padding
+ padding = get_pad_tuple2d(padding)
return _make.conv2d(data, kernel,
input_zero_point, kernel_zero_point,
input_scale, kernel_scale,
diff --git a/src/relay/qnn/op/convolution.cc b/src/relay/qnn/op/convolution.cc
index 91739e6..6626ce2 100644
--- a/src/relay/qnn/op/convolution.cc
+++ b/src/relay/qnn/op/convolution.cc
@@ -177,13 +177,17 @@ Expr Conv2DFallBack(const Expr& data, const Expr& weight, const Expr& input_zero
Expr Conv2DPadInput(const Expr& data, const Expr& input_zero_point, const Conv2DAttrs* param) {
// 1) Pad the input data
auto padded_data = data;
- auto pad_h_value = get_const_int(param->padding[0]);
- auto pad_w_value = get_const_int(param->padding[1]);
- if (pad_h_value != 0 || pad_w_value != 0) {
+ auto pad_top_value = get_const_int(param->padding[0]);
+ auto pad_left_value = get_const_int(param->padding[1]);
+ auto pad_bottom_value = get_const_int(param->padding[2]);
+ auto pad_right_value = get_const_int(param->padding[3]);
+ bool do_pad = pad_top_value != 0 || pad_left_value != 0 ||
+ pad_bottom_value != 0 || pad_right_value != 0;
+ if (do_pad) {
Array<IndexExpr> pad_n({0, 0});
Array<IndexExpr> pad_c({0, 0});
- Array<IndexExpr> pad_h({param->padding[0], param->padding[0]});
- Array<IndexExpr> pad_w({param->padding[1], param->padding[1]});
+ Array<IndexExpr> pad_h({param->padding[0], param->padding[2]});
+ Array<IndexExpr> pad_w({param->padding[1], param->padding[3]});
Array<Array<IndexExpr>> pad_width;
if (param->data_layout == "NCHW") {
@@ -336,7 +340,7 @@ Expr DepthwiseConv2DFourthTerm(int input_zero_point_int, int kernel_zero_point_i
*/
Expr Conv2DFirstTerm(const Expr& padded_data, const Expr& weight, const Conv2DAttrs* param) {
// Lowering for Term 1
- Array<IndexExpr> padding({0, 0});
+ Array<IndexExpr> padding({0, 0, 0, 0});
return Conv2D(padded_data, weight, param->strides, padding, param->dilation, param->groups,
param->channels, param->kernel_size, param->data_layout, param->kernel_layout,
param->out_layout, param->out_dtype);
@@ -583,7 +587,6 @@ Expr QnnConv2DCanonicalize(const Attrs& attrs, const Array<Expr>& new_args,
const auto* param = attrs.as<Conv2DAttrs>();
CHECK(param != nullptr);
// Assertion checks for exisiing support.
- CHECK_EQ(param->padding.size(), 2) << "qnn.conv2d only supports 2D padding";
CHECK(param->data_layout == "NCHW" || param->data_layout == "NHWC")
<< "qnn.conv2d supports only NCHW/NHWC input data layout.";
CHECK(param->kernel_layout == "OIHW" || param->kernel_layout == "HWIO" ||
diff --git a/tests/python/relay/test_op_qnn_conv2d.py b/tests/python/relay/test_op_qnn_conv2d.py
index 66acda8..6911c52 100644
--- a/tests/python/relay/test_op_qnn_conv2d.py
+++ b/tests/python/relay/test_op_qnn_conv2d.py
@@ -496,6 +496,30 @@ def test_padding():
verify(ref_func, qnn_func, data_shape, data_dtype,
kernel_shape, kernel_dtype)
+ # Try asymmetric padding
+ data_shape = (2, 2, 4, 4) # NHWC
+ data_dtype = 'uint8'
+ kernel_shape = (2, 2, 4, 3) # HWIO
+ kernel_dtype = 'uint8'
+ ref_func, qnn_func = get_funcs(data_shape=data_shape,
+ data_dtype=data_dtype,
+ kernel_shape=kernel_shape,
+ kernel_dtype=kernel_dtype,
+ input_zero_point=8,
+ kernel_zero_point=3,
+ input_scale=1.0,
+ kernel_scale=1.0,
+ kernel_size=(2, 2),
+ padding=(1, 1, 2, 2),
+ strides=(1, 1),
+ dilation=(1, 1),
+ data_layout="NHWC",
+ kernel_layout="HWIO",
+ out_dtype="int32")
+ verify(ref_func, qnn_func, data_shape, data_dtype,
+ kernel_shape, kernel_dtype)
+
+
def test_dilation():
with TempOpAttr("qnn.conv2d", "FTVMQnnLegalize", legalize_qnn_conv2d):