[GitHub] zhreshold commented on a change in pull request #13802: Image normalize operator - GPU support, 3D/4D inputs

[GitBox <gi...@apache.org>]

zhreshold commented on a change in pull request #13802: Image normalize operator - GPU support, 3D/4D inputs
URL: https://github.com/apache/incubator-mxnet/pull/13802#discussion_r247225013
 
 

 ##########
 File path: src/operator/image/normalize_op.cc
 ##########
 @@ -0,0 +1,83 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * \file normalize_op.cc
+ * \brief CPU Implementation of Normalize op
+ */
+#include "./normalize_op-inl.h"
+
+namespace mxnet {
+namespace op {
+namespace image {
+
+DMLC_REGISTER_PARAMETER(NormalizeParam);
+
+NNVM_REGISTER_OP(_image_normalize)
+.describe(R"code(Normalize an tensor of shape (C x H x W) or (N x C x H x W) with mean and
+    standard deviation.
+
+    Given mean `(m1, ..., mn)` and std `(s1, ..., sn)` for `n` channels,
+    this transform normalizes each channel of the input tensor with:
+.. math::
+        
+        output[i] = (input[i] - mi) / si
+    
+    If mean or std is scalar, the same value will be applied to all channels.
+
+Example:
+
+    .. code-block:: python
+        image = mx.nd.random.uniform(0, 1, (3, 4, 2))
+        normalize(image, mean=(0, 1, 2), std=(3, 2, 1))
+            [[[ 0.18293785  0.19761486]
+              [ 0.23839645  0.28142193]
+              [ 0.20092112  0.28598186]
+              [ 0.18162774  0.28241724]]
+             [[-0.2881726  -0.18821815]
+              [-0.17705294 -0.30780914]
+              [-0.2812064  -0.3512327 ]
+              [-0.05411351 -0.4716435 ]]
+             [[-1.0363373  -1.7273437 ]
+              [-1.6165586  -1.5223348 ]
+              [-1.208275   -1.1878313 ]
+              [-1.4711051  -1.5200229 ]]]
+            <NDArray 3x4x2 @cpu(0)>
+)code" ADD_FILELINE)
+.set_attr_parser(ParamParser<NormalizeParam>)
+.set_num_inputs(1)
+.set_num_outputs(1)
+.set_attr<nnvm::FListInputNames>("FListInputNames",
+  [](const NodeAttrs& attrs) {
+    return std::vector<std::string>{"data"};
+  })
+.set_attr<nnvm::FInferShape>("FInferShape", NormalizeOpShape)
+.set_attr<nnvm::FInferType>("FInferType", NormalizeOpType)
+.set_attr<FCompute>("FCompute<cpu>", NormalizeOpForward<cpu>)
+.set_attr<nnvm::FInplaceOption>("FInplaceOption",
+  [](const NodeAttrs& attrs) {
+    return std::vector<std::pair<int, int> >{{0, 0}};
+  })
+.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseNone{ "_copy" })
 
 Review comment:
   copy gradient is not correct IMO, even though this OP rarely pass gradient back, we still need to take care of this

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