From 46cbd0f860eac39dc82e87bee21c60395601349a Mon Sep 17 00:00:00 2001
From: Vandana Kannan <vandana268@gmail.com>
Date: Sat, 24 Aug 2019 12:11:23 -0700
Subject: [PATCH 1/2] ONNX import/export: Upsampling

---
 .../contrib/onnx/mx2onnx/_op_translations.py  | 27 +++++++++++++++++++
 .../contrib/onnx/onnx2mx/_import_helper.py    |  5 ++--
 .../contrib/onnx/onnx2mx/_op_translations.py  | 21 +++++++++++++++
 tests/python-pytest/onnx/test_cases.py        |  3 ++-
 4 files changed, 53 insertions(+), 3 deletions(-)

diff --git a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
index 35f4ff451cdb..098b8e5b9278 100644
--- a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
+++ b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
@@ -2047,3 +2047,30 @@ def convert_broadcast_to(node, **kwargs):
     )
 
     return [tensor_node, expand_node]
+
+
+@mx_op.register("UpSampling")
+def convert_upsample(node, **kwargs):
+    """Map MXNet's UpSampling operator attributes to onnx's Upsample operator
+    and return the created node.
+    """
+    name, input_nodes, attrs = get_inputs(node, kwargs)
+
+    sample_type = attrs.get('sample_type', 'nearest')
+    sample_type = 'linear' if sample_type == 'bilinear' else sample_type
+    scale = convert_string_to_list(attrs.get('scale'))
+    scaleh = float(scale[0])
+    scalew = float(scale[0])
+    if len(scale) > 1:
+        scalew = float(scale[1])
+    scale = [1.0, 1.0, scaleh, scalew]
+
+    node = onnx.helper.make_node(
+        'Upsample',
+        input_nodes,
+        [name],
+        scales=scale,
+        mode=sample_type,
+        name=name
+    )
+    return [node]
diff --git a/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py b/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py
index cf95bfef09a3..939027b12d51 100644
--- a/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py
+++ b/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py
@@ -23,7 +23,7 @@
 from ._op_translations import tanh, arccos, arcsin, arctan, _cos, _sin, _tan
 from ._op_translations import softplus, shape, gather, lp_pooling, size
 from ._op_translations import ceil, floor, hardsigmoid, global_lppooling
-from ._op_translations import concat, hardmax
+from ._op_translations import concat, hardmax, upsampling
 from ._op_translations import leaky_relu, _elu, _prelu, _selu, softmax, fully_connected
 from ._op_translations import global_avgpooling, global_maxpooling, linalg_gemm
 from ._op_translations import sigmoid, pad, relu, matrix_multiplication, batch_norm
@@ -147,5 +147,6 @@
     'DepthToSpace'      : depthtospace,
     'SpaceToDepth'      : spacetodepth,
     'Hardmax'           : hardmax,
-    'LpNormalization'   : lpnormalization
+    'LpNormalization'   : lpnormalization,
+    'Upsample'          : upsampling
 }
diff --git a/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py b/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
index 734b438581a5..4c5b8874d241 100644
--- a/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
+++ b/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
@@ -779,3 +779,24 @@ def lpnormalization(attrs, inputs, proto_obj):
     axis = int(attrs.get("axis", -1))
     new_attrs.update(axis=axis)
     return 'norm', new_attrs, inputs
+
+
+def upsampling(attrs, inputs, proto_obj):
+    """Rearranges blocks of spatial data into depth."""
+    new_attrs = translation_utils._fix_attribute_names(attrs, {'scales': 'scale',
+                                                               'mode': 'sample_type'})
+    sample_type = new_attrs.get('sample_type', 'nearest')
+    if sample_type != 'nearest':
+        raise NotImplementedError("Operator {} in ONNX supports 'linear' mode "
+                                  "for linear, bilinear, trilinear etc. There is no "
+                                  "way to distinguish these so far. Therefore, supporting "
+                                  "import of only nearest neighbor upsampling for now. "
+                                  "/~https://github.com/onnx/onnx/issues/1774. "
+                                  "Use contrib.BilinearResize2D for bilinear mode."
+                                  .format('UpSample'))
+
+    scale = tuple(new_attrs.get('scale'))[2:]
+    scale = tuple([int(s) for s in scale])
+    mx_op = symbol.UpSampling(inputs[0], scale=scale, sample_type=sample_type)
+
+    return mx_op, new_attrs, inputs
diff --git a/tests/python-pytest/onnx/test_cases.py b/tests/python-pytest/onnx/test_cases.py
index 89b60d15e84f..90136bb01ba6 100644
--- a/tests/python-pytest/onnx/test_cases.py
+++ b/tests/python-pytest/onnx/test_cases.py
@@ -78,7 +78,8 @@
              'test_max_',
              'test_softplus',
              'test_reduce_',
-             'test_split_equal'
+             'test_split_equal',
+             'test_upsample_n'
              ],
     'import': ['test_gather',
                'test_softsign',

From 36ecf8dff0f02be1624def320ec69cfaaf5b0897 Mon Sep 17 00:00:00 2001
From: Vandana Kannan <vandana268@gmail.com>
Date: Tue, 27 Aug 2019 10:34:59 -0700
Subject: [PATCH 2/2] Re-trigger CI