sandeep-krishnamurthy closed pull request #13717: ONNX import: Hardmax
URL: https://github.com/apache/incubator-mxnet/pull/13717
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diff --git a/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py
b/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py
index 2ceabaec1dc..5b33f9faac1 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
+from ._op_translations import concat, hardmax
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
@@ -144,5 +144,6 @@
'HardSigmoid' : hardsigmoid,
'LpPool' : lp_pooling,
'DepthToSpace' : depthtospace,
- 'SpaceToDepth' : spacetodepth
+ 'SpaceToDepth' : spacetodepth,
+ 'Hardmax' : hardmax
}
diff --git a/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
b/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
index 70283252931..ce0e0e51ef7 100644
--- a/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
+++ b/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
@@ -714,3 +714,29 @@ def spacetodepth(attrs, inputs, proto_obj):
new_attrs = translation_utils._fix_attribute_names(attrs,
{'blocksize':'block_size'})
return "space_to_depth", new_attrs, inputs
+
+
+def hardmax(attrs, inputs, proto_obj):
+ """Returns batched one-hot vectors."""
+ input_tensor_data = proto_obj.model_metadata.get('input_tensor_data')[0]
+ input_shape = input_tensor_data[1]
+
+ axis = int(attrs.get('axis', 1))
+ axis = axis if axis >= 0 else len(input_shape) + axis
+
+ if axis == len(input_shape) - 1:
+ amax = symbol.argmax(inputs[0], axis=-1)
+ one_hot = symbol.one_hot(amax, depth=input_shape[-1])
+ return one_hot, attrs, inputs
+
+ # since reshape doesn't take a tensor for shape,
+ # computing with np.prod. This needs to be changed to
+ # to use mx.sym.prod() when mx.sym.reshape() is fixed.
+ # (https://github.com/apache/incubator-mxnet/issues/10789)
+ new_shape = (int(np.prod(input_shape[:axis])),
+ int(np.prod(input_shape[axis:])))
+ reshape_op = symbol.reshape(inputs[0], new_shape)
+ amax = symbol.argmax(reshape_op, axis=-1)
+ one_hot = symbol.one_hot(amax, depth=new_shape[-1])
+ hardmax_op = symbol.reshape(one_hot, input_shape)
+ return hardmax_op, attrs, inputs
diff --git a/tests/python-pytest/onnx/test_cases.py
b/tests/python-pytest/onnx/test_cases.py
index 92e80e05670..6a189b62492 100644
--- a/tests/python-pytest/onnx/test_cases.py
+++ b/tests/python-pytest/onnx/test_cases.py
@@ -90,7 +90,8 @@
'test_averagepool_2d_strides',
'test_averagepool_3d',
'test_LpPool_',
- 'test_split_equal'
+ 'test_split_equal',
+ 'test_hardmax'
],
'export': ['test_random_uniform',
'test_random_normal',
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